Nothing
tests/testthat/test-regplots.R
In procs: Recreates Some 'SAS®' Procedures in 'R'
cls <- read.table(header = TRUE, text = '
Name Sex Age Height Weight
Alfred M 14 69 112.5
Alice F 13 56.5 84
Barbara F 13 65.3 98
Carol F 14 62.8 102.5
Henry M 14 63.5 102.5
James M 12 57.3 83
Jane F 12 59.8 84.5
Janet F 15 62.5 112.5
Jeffrey M 13 62.5 84
John M 12 59 99.5
Joyce F 11 51.3 50.5
Judy F 14 64.3 90
Louise F 12 56.3 77
Mary F 15 66.5 112
Philip M 16 72 150
Robert M 12 64.8 128
Ronald M 15 67 133
Thomas M 11 57.5 85
William M 15 66.5 112')
hrdat <- read.table(header = TRUE, text = '
Region Eyes Hair Count
1 blue fair 23
1 blue dark 11
1 green medium 18
1 brown red 5
1 brown black 3
2 blue medium 44
2 green fair 50
2 green dark 23
2 brown medium 53
1 blue red 7
1 green fair 19
1 green dark 14
1 brown medium 41
2 blue fair 46
2 blue dark 40
2 green red 31
2 brown fair 56
2 brown dark 54
1 blue medium 24
1 green red 7
1 brown fair 34
1 brown dark 40
2 blue red 21
2 blue black 6
2 green medium 37
2 brown red 42
2 brown black 13
')
clsna <- read.table(header = TRUE, text = '
Name Sex Age Height Weight region
Alfred M 14 69.0 112.5 A
Alice F 13 56.5 84.0 A
Barbara F 13 65.3 98.0 A
Carol F 14 62.8 102.5 A
Henry M 14 63.5 102.5 A
James M 12 NA 83.0 A
Jane NA 12 59.8 84.5 A
Janet F 15 62.5 112.5 A
Jeffrey M 13 62.5 84.0 A
John M 12 59.0 99.5 B
Joyce F 11 51.3 50.5 B
Judy F 14 64.3 90.0 B
Louise F 12 56.3 NA B
Mary F 15 66.5 112.0 B
Philip M 16 72.0 150.0 B
Robert M 12 64.8 128.0 B
Ronald M 15 67.0 133.0 B
Thomas M 11 57.5 85.0 B
William M 15 66.5 112.0 B')
options("logr.output" = FALSE)
options("procs.print" = FALSE)
dev <- FALSE
test_that("regplot1: regplot() object works as expected.", {
res <- regplot()
res
expect_equal("regplot" %in% class(res), TRUE)
expect_equal(res$stats, "default")
expect_equal(res$panel, TRUE)
expect_equal(res$type, c("diagnostics", "residuals", "fitplot"))
res <- regplot(type = c("residuals", "fitplot"),
stats = "default",
panel = FALSE)
res
expect_equal("regplot" %in% class(res), TRUE)
expect_equal(res$stats, "default")
expect_equal(res$panel, FALSE)
expect_equal(res$type, c("residuals", "fitplot"))
})
# This plot gets split if there are multiple independent variables.
test_that("regplot2: works for residuals", {
# One independant variable
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Two independent variables
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
if (dev) {
cls2 <- cls
cls2$Sample1 <- round(runif(19, 50, 100))
cls2$Sample2 <- round(runif(19, 50, 100))
cls2$Sample3 <- round(runif(19, 50, 100))
cls2$Sample4 <- round(runif(19, 50, 100))
cls2$Sample5 <- round(runif(19, 50, 100))
cls2$Sample6 <- round(runif(19, 50, 100))
cls2$Sample7 <- round(runif(19, 50, 100))
cls2$Sample8 <- round(runif(19, 50, 100))
cls2$Sample9 <- round(runif(19, 50, 100))
cls2$Sample10 <- round(runif(19, 50, 100))
# Four independent variables
res <- proc_reg(cls2,
model = "Weight = Height Age Sample1 Sample2",
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Seven independent variables
res <- proc_reg(cls2,
model = "Weight = Height Age Sample1 Sample2 Sample3 Sample4 Sample5 Sample6",
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Twelve independent variables
# Two charts
mdl <- paste0("Weight = Height Age Sample1 Sample2 Sample3 Sample4 ",
"Sample5 Sample6 Sample7 Sample8 Sample9 Sample10")
res <- proc_reg(cls2,
model = mdl,
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
}
})
# Good.
test_that("regplot3: works for fitplot.", {
# 95% Confidence
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# 90% Confidence
proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot"),
options = v(alpha = .1))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Should produce no plot because of two independent variables
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "fitplot"))
expect_equal(length(res), 4)
# Custom statistics
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot", stats =
c("nobs", "aic", "rsquare")),
options = v(alpha = .1))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# No statistics
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot", stats = "none"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot4: works for multiple plots.", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = c("diagnostics",
"residuals",
"fitplot")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Got these matching!
test_that("regplot5: works for qqplot", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "qqplot") #,
# stats = p
)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "qqplot") #,
# stats = p
)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight",
output = report,
plots = regplot(type = "qqplot") #,
# stats = p
)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight Age",
output = report,
plots = regplot(type = "qqplot") #,
# stats = p
)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# OK
test_that("regplot6: works for rfplot plot", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "rfplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "rfplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight",
output = report,
plots = regplot(type = "rfplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight Age",
output = report,
plots = regplot(type = "rfplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Works
test_that("regplot7: panel = FALSE works", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics", panel = FALSE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal(length(res[[5]]) > 1, TRUE)
})
# Good
test_that("regplot8: works for cooksd plot", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "cooksd"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels
res2 <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "cooksd",
label = TRUE, id = "Name"))
expect_equal(length(res2), 5)
expect_equal("plot_spec" %in% class(res2[[5]][[1]]), TRUE)
})
# Good
test_that("regplot9: works for residualbypredicted", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "residualbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Seems good. Worry about whether it is always +2 and -2 for boundary lines.
# +2 and -2 appears to be standard deviation. It can be changed on the rstudent
# function, but no obvious parameter on SAS chart. So probably OK.
test_that("regplot10: works for rstudentbypredicted", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels for outliers - Works!
res2 <- proc_reg(iris,
model = Sepal.Length ~ Petal.Length,
output = report,
plots = regplot(type = "rstudentbypredicted",
label = TRUE))
expect_equal(length(res2), 5)
expect_equal("plot_spec" %in% class(res2[[5]][[1]]), TRUE)
# Error check
expect_error(proc_reg(iris,
model = Sepal.Length ~ Petal.Length,
output = report,
plots = regplot(type = "rstudentbypredicted",
label = TRUE, id = "fork")))
})
# Looks good.
test_that("regplot11: works for rstudentbyleverage", {
# Class data
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbyleverage"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# More data points - Wow, great!
res2 <- proc_reg(iris, model = Sepal.Length ~ Petal.Length,
output = report,
stats = p,
plots = regplot(type = "rstudentbyleverage"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# More data
res3 <- proc_reg(mtcars, model = mpg ~ disp,
output = report,
plots = regplot(type = "rstudentbyleverage"))
expect_equal(length(res3), 5)
expect_equal("plot_spec" %in% class(res3[[5]][[1]]), TRUE)
# Two independent variables - Still works!
res3 <- proc_reg(mtcars, model = mpg ~ hp + disp,
output = report,
plots = regplot(type = "rstudentbyleverage"))
expect_equal(length(res3), 5)
expect_equal("plot_spec" %in% class(res3[[5]][[1]]), TRUE)
})
test_that("regplot12: works for rstudentbyleverage with labels and id", {
# Assigned label - Awesome!
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbyleverage",
label = TRUE, id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Default label
res2 <- proc_reg(iris, model = Sepal.Length ~ Petal.Length,
output = report,
plots = regplot(type = "rstudentbyleverage",
label = TRUE))
expect_equal(length(res2), 5)
expect_equal("plot_spec" %in% class(res2[[5]][[1]]), TRUE)
# Big labels
cdt <- mtcars
cdt$name <- rownames(mtcars)
res3 <- proc_reg(cdt, model = mpg ~ disp,
output = report,
plots = regplot(type = "rstudentbyleverage",
label = TRUE, id = "name"))
expect_equal(length(res3), 5)
expect_equal("plot_spec" %in% class(res3[[5]][[1]]), TRUE)
# Two independent variables - Still works!
res4 <- proc_reg(cdt, model = mpg ~ hp + disp,
output = report,
plots = regplot(type = "rstudentbyleverage",
label = TRUE, id = "name"))
expect_equal(length(res4), 5)
expect_equal("plot_spec" %in% class(res4[[5]][[1]]), TRUE)
})
# X and Y Scales have to be the same.
# Margins also matter. Margins can change slope of line.
test_that("regplot13: works for observedbypredicted", {
# OK
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "observedbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# OK
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "observedbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# OK
res <- proc_reg(cls,
model = "Age = Weight",
output = report,
plots = regplot(type = "observedbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# OK
res <- proc_reg(cls,
model = "Age = Height",
output = report,
plots = regplot(type = "observedbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Bins will not match. Using Sturges algoritm instead.
test_that("regplot14: works for residualhistogram", {
#
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight",
output = report,
plots = regplot(type = "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight Age",
output = report,
plots = regplot(type = "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot15: passing type strings works.", {
# Pass quoted string type
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = "residualhistogram")
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Quoted string
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = "residualhistogram")
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# v function
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = v(fitplot, residuals, residualhistogram))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Vector of strings
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = c("fitplot", "residuals", "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# This is amazing
test_that("regplot16: works for diagnostics", {
# One variable
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Two independent variables
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "diagnostics"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Control stats
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics",
stats = c("default", "aic")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# No stats
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics",
stats = "none"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels no ID
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels with ID
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics", label = TRUE,
id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot17: edge cases.", {
# New data
res <- proc_reg(iris,
model = "Sepal.Length = Petal.Length",
output = report,
plots = regplot(type = c("diagnostics", "residualhistogram",
"cooksd"), label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# New data
res <- proc_reg(iris,
model = "Sepal.Length = Petal.Length",
output = report,
plots = regplot(type = c("diagnostics", "residualhistogram",
"residuals"), label = TRUE,
panel = FALSE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Multiple models
res <- proc_reg(iris, model = c("Sepal.Length = Petal.Length",
"Sepal.Length = Sepal.Width",
"Sepal.Length = Petal.Width"),
output = report,
plots = "diagnostics",
titles = "Iris Regression Statistics")
expect_equal(length(res), 3) # 3 Models
expect_equal("plot_spec" %in% class(res[[1]][[5]][[1]]), TRUE)
})
test_that("regplot18: statistics work as expected.", {
# ADJRSQ, AIC, BIC, COEFFVAR, CP, DEFAULT, DEPMEAN, EDF, GMSEP, JP,
# MSE, NOBS, NPARM, PC, RSQUARE, SBC, SP, SSE
res <- proc_reg(cls,
model = Weight ~ Height,
output = report,
plots = regplot(type = "diagnostics",
stats = c("nobs", "edf", "rsquare", "adjrsq",
"nparm", "coeffvar", "mse", "depmean")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = Weight ~ Height,
output = report,
plots = regplot(type = "diagnostics",
stats = c("nobs", "aic", "sse")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = Weight ~ Height,
output = report,
plots = regplot(type = "fitplot",
stats = c("nobs", "aic", "sse")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# fit <- lm(Weight ~ Age , cls)
#
# avl <- extractAIC(fit)
#
# avl
#
# bvl <- extractAIC(fit, k = log(nrow(cls)))
#
# bvl
#
# bvl2 <- BIC(fit) # Can't get BIC to work
#
# bvl3 <- extractAIC(fit, log(nrow(cls)))
})
# Works
test_that("regplot19: works for residualboxplot", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualboxplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "residualboxplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Works
test_that("regplot20: works for TRUE and 'all'", {
# plots = TRUE
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = TRUE)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# All
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = 'all')
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# All with label and id
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot('all', label = TRUE, id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot21: works for dffits", {
# Basic
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dffits"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dffits", label = TRUE, id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# No ID variable
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dffits", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# New data - Awesome
res <- proc_reg(iris,
model = "Sepal.Length = Petal.Length",
output = report,
plots = regplot(type = "dffits", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot22: works for dfbetas", {
# Basic
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dfbetas"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dfbetas", label = TRUE, id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# No ID variable
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dfbetas", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# New data - Awesome
res <- proc_reg(iris,
model = "Sepal.Length = Petal.Length",
output = report,
plots = regplot(type = "dfbetas", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot23: dfbetas multiple dependent variables", {
cls2 <- cls
cls$Sample1 <- runif(nrow(cls2), 50, 100)
cls$Sample2 <- runif(nrow(cls2), 50, 100)
cls$Sample3 <- runif(nrow(cls2), 50, 100)
cls$Sample4 <- runif(nrow(cls2), 50, 100)
cls$Sample5 <- runif(nrow(cls2), 50, 100)
cls$Sample6 <- runif(nrow(cls2), 50, 100)
cls$Sample7 <- runif(nrow(cls2), 50, 100)
cls$Sample8 <- runif(nrow(cls2), 50, 100)
cls$Sample9 <- runif(nrow(cls2), 50, 100)
# 4 variables
res <- proc_reg(cls,
model = "Weight = Height Age Sample1",
output = report,
plots = regplot(type = "dfbetas"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# 6 variables
res <- proc_reg(cls,
model = "Weight = Height Sample1 Sample2 Sample3 Sample4",
output = report,
plots = regplot(type = "dfbetas"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# 9 variables
res <- proc_reg(cls,
model = "Weight = Height Sample1 Sample2 Sample3 Sample4 Sample5 Sample6 Sample7",
output = report,
plots = regplot(type = "dfbetas"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[2]]), TRUE)
# 3 variables - panel = FALSE
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = FALSE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[2]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[3]]), TRUE)
# 3 variables - panel = FALSE and labels
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = FALSE, label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[2]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[3]]), TRUE)
# 3 variables - panel = FALSE, labels, and id
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = FALSE, label = TRUE,
id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[2]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[3]]), TRUE)
# 3 variables - panel = TRUE, labels
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = TRUE, label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# 3 variables - panel = TRUE, labels, and id
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = TRUE, label = TRUE,
id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# multiple models, cooksd with labels
res <- proc_reg(cls,
output = report,
model = list(Weight ~ Height,
Height ~ Weight),
plots = regplot(type = c("cooksd"),
label = TRUE, id = "Name"))
expect_equal(length(res), 2)
expect_equal(length(res[[1]]), 5)
expect_equal("plot_spec" %in% class(res[[1]][[5]][[1]]), TRUE)
})
test_that("regplot24: remove_na_rows works as expected", {
expect_equal(nrow(clsna), 19)
res <- remove_na_rows(clsna, "Weight", c("Height", "Age"))
expect_equal(nrow(res), 17)
})
test_that("regplot24: Test NAs on all plots", {
# One independent variable
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualhistogram")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "observedbypredicted")) # Fixed
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics")) # Fixed
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "cooksd")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "dfbetas")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "dffits")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot")) # Fixed
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "qqplot")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "residuals")) # Fixed
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualbypredicted")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "rfplot")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbyleverage")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbypredicted")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "all")) # Yes
# Great
res <- proc_reg(clsna,
model = "Weight = Height",
by = "Sex",
output = report,
plots = regplot(type = "all"))
# Any errors above will cause test to fail
expect_equal(TRUE, TRUE)
})
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cls <- read.table(header = TRUE, text = '
Name Sex Age Height Weight
Alfred M 14 69 112.5
Alice F 13 56.5 84
Barbara F 13 65.3 98
Carol F 14 62.8 102.5
Henry M 14 63.5 102.5
James M 12 57.3 83
Jane F 12 59.8 84.5
Janet F 15 62.5 112.5
Jeffrey M 13 62.5 84
John M 12 59 99.5
Joyce F 11 51.3 50.5
Judy F 14 64.3 90
Louise F 12 56.3 77
Mary F 15 66.5 112
Philip M 16 72 150
Robert M 12 64.8 128
Ronald M 15 67 133
Thomas M 11 57.5 85
William M 15 66.5 112')
hrdat <- read.table(header = TRUE, text = '
Region Eyes Hair Count
1 blue fair 23
1 blue dark 11
1 green medium 18
1 brown red 5
1 brown black 3
2 blue medium 44
2 green fair 50
2 green dark 23
2 brown medium 53
1 blue red 7
1 green fair 19
1 green dark 14
1 brown medium 41
2 blue fair 46
2 blue dark 40
2 green red 31
2 brown fair 56
2 brown dark 54
1 blue medium 24
1 green red 7
1 brown fair 34
1 brown dark 40
2 blue red 21
2 blue black 6
2 green medium 37
2 brown red 42
2 brown black 13
')
clsna <- read.table(header = TRUE, text = '
Name Sex Age Height Weight region
Alfred M 14 69.0 112.5 A
Alice F 13 56.5 84.0 A
Barbara F 13 65.3 98.0 A
Carol F 14 62.8 102.5 A
Henry M 14 63.5 102.5 A
James M 12 NA 83.0 A
Jane NA 12 59.8 84.5 A
Janet F 15 62.5 112.5 A
Jeffrey M 13 62.5 84.0 A
John M 12 59.0 99.5 B
Joyce F 11 51.3 50.5 B
Judy F 14 64.3 90.0 B
Louise F 12 56.3 NA B
Mary F 15 66.5 112.0 B
Philip M 16 72.0 150.0 B
Robert M 12 64.8 128.0 B
Ronald M 15 67.0 133.0 B
Thomas M 11 57.5 85.0 B
William M 15 66.5 112.0 B')
options("logr.output" = FALSE)
options("procs.print" = FALSE)
dev <- FALSE
test_that("regplot1: regplot() object works as expected.", {
res <- regplot()
res
expect_equal("regplot" %in% class(res), TRUE)
expect_equal(res$stats, "default")
expect_equal(res$panel, TRUE)
expect_equal(res$type, c("diagnostics", "residuals", "fitplot"))
res <- regplot(type = c("residuals", "fitplot"),
stats = "default",
panel = FALSE)
res
expect_equal("regplot" %in% class(res), TRUE)
expect_equal(res$stats, "default")
expect_equal(res$panel, FALSE)
expect_equal(res$type, c("residuals", "fitplot"))
})
# This plot gets split if there are multiple independent variables.
test_that("regplot2: works for residuals", {
# One independant variable
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Two independent variables
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
if (dev) {
cls2 <- cls
cls2$Sample1 <- round(runif(19, 50, 100))
cls2$Sample2 <- round(runif(19, 50, 100))
cls2$Sample3 <- round(runif(19, 50, 100))
cls2$Sample4 <- round(runif(19, 50, 100))
cls2$Sample5 <- round(runif(19, 50, 100))
cls2$Sample6 <- round(runif(19, 50, 100))
cls2$Sample7 <- round(runif(19, 50, 100))
cls2$Sample8 <- round(runif(19, 50, 100))
cls2$Sample9 <- round(runif(19, 50, 100))
cls2$Sample10 <- round(runif(19, 50, 100))
# Four independent variables
res <- proc_reg(cls2,
model = "Weight = Height Age Sample1 Sample2",
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Seven independent variables
res <- proc_reg(cls2,
model = "Weight = Height Age Sample1 Sample2 Sample3 Sample4 Sample5 Sample6",
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Twelve independent variables
# Two charts
mdl <- paste0("Weight = Height Age Sample1 Sample2 Sample3 Sample4 ",
"Sample5 Sample6 Sample7 Sample8 Sample9 Sample10")
res <- proc_reg(cls2,
model = mdl,
output = report,
plots = regplot(type = "residuals"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
}
})
# Good.
test_that("regplot3: works for fitplot.", {
# 95% Confidence
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# 90% Confidence
proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot"),
options = v(alpha = .1))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Should produce no plot because of two independent variables
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "fitplot"))
expect_equal(length(res), 4)
# Custom statistics
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot", stats =
c("nobs", "aic", "rsquare")),
options = v(alpha = .1))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# No statistics
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot", stats = "none"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot4: works for multiple plots.", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = c("diagnostics",
"residuals",
"fitplot")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Got these matching!
test_that("regplot5: works for qqplot", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "qqplot") #,
# stats = p
)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "qqplot") #,
# stats = p
)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight",
output = report,
plots = regplot(type = "qqplot") #,
# stats = p
)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight Age",
output = report,
plots = regplot(type = "qqplot") #,
# stats = p
)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# OK
test_that("regplot6: works for rfplot plot", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "rfplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "rfplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight",
output = report,
plots = regplot(type = "rfplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight Age",
output = report,
plots = regplot(type = "rfplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Works
test_that("regplot7: panel = FALSE works", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics", panel = FALSE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal(length(res[[5]]) > 1, TRUE)
})
# Good
test_that("regplot8: works for cooksd plot", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "cooksd"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels
res2 <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "cooksd",
label = TRUE, id = "Name"))
expect_equal(length(res2), 5)
expect_equal("plot_spec" %in% class(res2[[5]][[1]]), TRUE)
})
# Good
test_that("regplot9: works for residualbypredicted", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "residualbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Seems good. Worry about whether it is always +2 and -2 for boundary lines.
# +2 and -2 appears to be standard deviation. It can be changed on the rstudent
# function, but no obvious parameter on SAS chart. So probably OK.
test_that("regplot10: works for rstudentbypredicted", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels for outliers - Works!
res2 <- proc_reg(iris,
model = Sepal.Length ~ Petal.Length,
output = report,
plots = regplot(type = "rstudentbypredicted",
label = TRUE))
expect_equal(length(res2), 5)
expect_equal("plot_spec" %in% class(res2[[5]][[1]]), TRUE)
# Error check
expect_error(proc_reg(iris,
model = Sepal.Length ~ Petal.Length,
output = report,
plots = regplot(type = "rstudentbypredicted",
label = TRUE, id = "fork")))
})
# Looks good.
test_that("regplot11: works for rstudentbyleverage", {
# Class data
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbyleverage"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# More data points - Wow, great!
res2 <- proc_reg(iris, model = Sepal.Length ~ Petal.Length,
output = report,
stats = p,
plots = regplot(type = "rstudentbyleverage"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# More data
res3 <- proc_reg(mtcars, model = mpg ~ disp,
output = report,
plots = regplot(type = "rstudentbyleverage"))
expect_equal(length(res3), 5)
expect_equal("plot_spec" %in% class(res3[[5]][[1]]), TRUE)
# Two independent variables - Still works!
res3 <- proc_reg(mtcars, model = mpg ~ hp + disp,
output = report,
plots = regplot(type = "rstudentbyleverage"))
expect_equal(length(res3), 5)
expect_equal("plot_spec" %in% class(res3[[5]][[1]]), TRUE)
})
test_that("regplot12: works for rstudentbyleverage with labels and id", {
# Assigned label - Awesome!
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbyleverage",
label = TRUE, id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Default label
res2 <- proc_reg(iris, model = Sepal.Length ~ Petal.Length,
output = report,
plots = regplot(type = "rstudentbyleverage",
label = TRUE))
expect_equal(length(res2), 5)
expect_equal("plot_spec" %in% class(res2[[5]][[1]]), TRUE)
# Big labels
cdt <- mtcars
cdt$name <- rownames(mtcars)
res3 <- proc_reg(cdt, model = mpg ~ disp,
output = report,
plots = regplot(type = "rstudentbyleverage",
label = TRUE, id = "name"))
expect_equal(length(res3), 5)
expect_equal("plot_spec" %in% class(res3[[5]][[1]]), TRUE)
# Two independent variables - Still works!
res4 <- proc_reg(cdt, model = mpg ~ hp + disp,
output = report,
plots = regplot(type = "rstudentbyleverage",
label = TRUE, id = "name"))
expect_equal(length(res4), 5)
expect_equal("plot_spec" %in% class(res4[[5]][[1]]), TRUE)
})
# X and Y Scales have to be the same.
# Margins also matter. Margins can change slope of line.
test_that("regplot13: works for observedbypredicted", {
# OK
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "observedbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# OK
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "observedbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# OK
res <- proc_reg(cls,
model = "Age = Weight",
output = report,
plots = regplot(type = "observedbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# OK
res <- proc_reg(cls,
model = "Age = Height",
output = report,
plots = regplot(type = "observedbypredicted"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Bins will not match. Using Sturges algoritm instead.
test_that("regplot14: works for residualhistogram", {
#
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight",
output = report,
plots = regplot(type = "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Height = Weight Age",
output = report,
plots = regplot(type = "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot15: passing type strings works.", {
# Pass quoted string type
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = "residualhistogram")
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Quoted string
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = "residualhistogram")
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# v function
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = v(fitplot, residuals, residualhistogram))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Vector of strings
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = c("fitplot", "residuals", "residualhistogram"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# This is amazing
test_that("regplot16: works for diagnostics", {
# One variable
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Two independent variables
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "diagnostics"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Control stats
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics",
stats = c("default", "aic")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# No stats
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics",
stats = "none"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels no ID
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels with ID
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics", label = TRUE,
id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot17: edge cases.", {
# New data
res <- proc_reg(iris,
model = "Sepal.Length = Petal.Length",
output = report,
plots = regplot(type = c("diagnostics", "residualhistogram",
"cooksd"), label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# New data
res <- proc_reg(iris,
model = "Sepal.Length = Petal.Length",
output = report,
plots = regplot(type = c("diagnostics", "residualhistogram",
"residuals"), label = TRUE,
panel = FALSE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Multiple models
res <- proc_reg(iris, model = c("Sepal.Length = Petal.Length",
"Sepal.Length = Sepal.Width",
"Sepal.Length = Petal.Width"),
output = report,
plots = "diagnostics",
titles = "Iris Regression Statistics")
expect_equal(length(res), 3) # 3 Models
expect_equal("plot_spec" %in% class(res[[1]][[5]][[1]]), TRUE)
})
test_that("regplot18: statistics work as expected.", {
# ADJRSQ, AIC, BIC, COEFFVAR, CP, DEFAULT, DEPMEAN, EDF, GMSEP, JP,
# MSE, NOBS, NPARM, PC, RSQUARE, SBC, SP, SSE
res <- proc_reg(cls,
model = Weight ~ Height,
output = report,
plots = regplot(type = "diagnostics",
stats = c("nobs", "edf", "rsquare", "adjrsq",
"nparm", "coeffvar", "mse", "depmean")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = Weight ~ Height,
output = report,
plots = regplot(type = "diagnostics",
stats = c("nobs", "aic", "sse")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = Weight ~ Height,
output = report,
plots = regplot(type = "fitplot",
stats = c("nobs", "aic", "sse")))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# fit <- lm(Weight ~ Age , cls)
#
# avl <- extractAIC(fit)
#
# avl
#
# bvl <- extractAIC(fit, k = log(nrow(cls)))
#
# bvl
#
# bvl2 <- BIC(fit) # Can't get BIC to work
#
# bvl3 <- extractAIC(fit, log(nrow(cls)))
})
# Works
test_that("regplot19: works for residualboxplot", {
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualboxplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "residualboxplot"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
# Works
test_that("regplot20: works for TRUE and 'all'", {
# plots = TRUE
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = TRUE)
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# All
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = 'all')
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# All with label and id
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot('all', label = TRUE, id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot21: works for dffits", {
# Basic
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dffits"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dffits", label = TRUE, id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# No ID variable
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dffits", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# New data - Awesome
res <- proc_reg(iris,
model = "Sepal.Length = Petal.Length",
output = report,
plots = regplot(type = "dffits", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot22: works for dfbetas", {
# Basic
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dfbetas"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# Labels
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dfbetas", label = TRUE, id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# No ID variable
res <- proc_reg(cls,
model = "Weight = Height",
output = report,
plots = regplot(type = "dfbetas", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# New data - Awesome
res <- proc_reg(iris,
model = "Sepal.Length = Petal.Length",
output = report,
plots = regplot(type = "dfbetas", label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
})
test_that("regplot23: dfbetas multiple dependent variables", {
cls2 <- cls
cls$Sample1 <- runif(nrow(cls2), 50, 100)
cls$Sample2 <- runif(nrow(cls2), 50, 100)
cls$Sample3 <- runif(nrow(cls2), 50, 100)
cls$Sample4 <- runif(nrow(cls2), 50, 100)
cls$Sample5 <- runif(nrow(cls2), 50, 100)
cls$Sample6 <- runif(nrow(cls2), 50, 100)
cls$Sample7 <- runif(nrow(cls2), 50, 100)
cls$Sample8 <- runif(nrow(cls2), 50, 100)
cls$Sample9 <- runif(nrow(cls2), 50, 100)
# 4 variables
res <- proc_reg(cls,
model = "Weight = Height Age Sample1",
output = report,
plots = regplot(type = "dfbetas"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# 6 variables
res <- proc_reg(cls,
model = "Weight = Height Sample1 Sample2 Sample3 Sample4",
output = report,
plots = regplot(type = "dfbetas"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# 9 variables
res <- proc_reg(cls,
model = "Weight = Height Sample1 Sample2 Sample3 Sample4 Sample5 Sample6 Sample7",
output = report,
plots = regplot(type = "dfbetas"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[2]]), TRUE)
# 3 variables - panel = FALSE
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = FALSE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[2]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[3]]), TRUE)
# 3 variables - panel = FALSE and labels
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = FALSE, label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[2]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[3]]), TRUE)
# 3 variables - panel = FALSE, labels, and id
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = FALSE, label = TRUE,
id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[2]]), TRUE)
expect_equal("plot_spec" %in% class(res[[5]][[3]]), TRUE)
# 3 variables - panel = TRUE, labels
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = TRUE, label = TRUE))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# 3 variables - panel = TRUE, labels, and id
res <- proc_reg(cls,
model = "Weight = Height Age",
output = report,
plots = regplot(type = "dfbetas", panel = TRUE, label = TRUE,
id = "Name"))
expect_equal(length(res), 5)
expect_equal("plot_spec" %in% class(res[[5]][[1]]), TRUE)
# multiple models, cooksd with labels
res <- proc_reg(cls,
output = report,
model = list(Weight ~ Height,
Height ~ Weight),
plots = regplot(type = c("cooksd"),
label = TRUE, id = "Name"))
expect_equal(length(res), 2)
expect_equal(length(res[[1]]), 5)
expect_equal("plot_spec" %in% class(res[[1]][[5]][[1]]), TRUE)
})
test_that("regplot24: remove_na_rows works as expected", {
expect_equal(nrow(clsna), 19)
res <- remove_na_rows(clsna, "Weight", c("Height", "Age"))
expect_equal(nrow(res), 17)
})
test_that("regplot24: Test NAs on all plots", {
# One independent variable
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualhistogram")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "observedbypredicted")) # Fixed
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "diagnostics")) # Fixed
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "cooksd")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "dfbetas")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "dffits")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "fitplot")) # Fixed
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "qqplot")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "residuals")) # Fixed
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "residualbypredicted")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "rfplot")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbyleverage")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "rstudentbypredicted")) # Yes
res <- proc_reg(clsna,
model = "Weight = Height",
output = report,
plots = regplot(type = "all")) # Yes
# Great
res <- proc_reg(clsna,
model = "Weight = Height",
by = "Sex",
output = report,
plots = regplot(type = "all"))
# Any errors above will cause test to fail
expect_equal(TRUE, TRUE)
})
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