inst/doc/MinimalRgg.R

In mosaic: Project MOSAIC Statistics and Mathematics Teaching Utilities

## ----setup,echo=FALSE,message=FALSE,include=FALSE-------------------
#source('setup.R')
require(mosaic)
require(parallel)
require(ggformula)
options(digits=4)
theme_set(theme_bw())
trellis.par.set(theme=col.mosaic())
set.seed(123)
#knit_hooks$set(inline = function(x) {
#	if (is.numeric(x)) return(knitr:::format_sci(x, 'latex'))
#	x = as.character(x)
#	h = knitr:::hilight_source(x, 'latex', list(prompt=FALSE, size='normalsize'))
#	h = gsub("([_#$%&])", "\\\\\\1", h)
#	h = gsub('(["\'])', '\\1{}', h)
#	gsub('^\\\\begin\\{alltt\\}\\s*|\\\\end\\{alltt\\}\\s*$', '', h)
#})
knitr::opts_chunk$set(
	dev="pdf",
	eval=FALSE,
	tidy=FALSE,
	fig.align='center',
	fig.show='hold',
	message=FALSE
	)

## -------------------------------------------------------------------
# apropos()
# ?
# ??
# example()

## -------------------------------------------------------------------
# # basic ops: + - * / ^ ( )
# log(); exp(); sqrt()

## ----highlight=FALSE------------------------------------------------
# log10(); abs(); choose()

## -------------------------------------------------------------------
# goal(y ~ x | z, data = mydata, ...)

## -------------------------------------------------------------------
# favstats()   # mosaic
# tally()      # mosaic
# mean()       # mosaic augmented
# median()     # mosaic augmented
# sd()         # mosaic augmented
# var()        # mosaic augmented
# diffmean()   # mosaic

## ----highlight=FALSE------------------------------------------------
# quantile()   # mosaic augmented
# prop()       # mosaic
# perc()       # mosaic
# rank()
# IQR()        # mosaic augmented
# min(); max() # mosaic augmented

## -------------------------------------------------------------------
# gf_boxplot()      # ggformula
# gf_point()        # ggformula
# gf_histogram()    # ggformula
# gf_density()      # ggformula
# gf_dens()         # ggformula
# gf_freqpol()      # ggformula
# gf_qq()           # ggformula
# gf_fun()          # ggformula
# makeFun()         # mosaic

## ----highlight=FALSE------------------------------------------------
# gf_dotplot()      # ggformula
# gf_bar()          # ggformula
# gf_col()          # ggformula

## ----eval=FALSE-----------------------------------------------------
# mplot(HELPrct)

## -------------------------------------------------------------------
# rflip()     # mosaic
# do()        # mosaic
# sample()    # mosaic augmented
# resample()  # with replacement
# shuffle()   # mosaic

## ----highlight=FALSE------------------------------------------------
# rbinom()
# rnorm()     # etc, if needed

## -------------------------------------------------------------------
# gf_dist()    # ggformula
# # plain
# pbinom(); pnorm();
# # mosaic augmented
# xpnorm(); xpchisq(); xpt()
# xqbinom(); xqnorm();
# xqchisq(); xqt()

## -------------------------------------------------------------------
# t.test()       # mosaic augmented
# binom.test()   # mosaic augmented
# prop.test()    # mosaic augmented
# xchisq.test()            # mosaic
# fisher.test()
# pval()                   # mosaic
# model <- lm()     # linear models
# summary(model)
# coef(model)
# confint(model) # mosaic augmented
# anova(model)
# makeFun(model)           # mosaic
# resid(model); fitted(model)
# gf_model(model)       # ggformula

## ----highlight=FALSE------------------------------------------------
# mplot(TukeyHSD(model))
# model <- glm() # logistic reg.

## -------------------------------------------------------------------
# nrow(); ncol(); dim()
# inspect()            # mosaic
# names()
# head(); tail()
# factor()

## ----highlight=FALSE------------------------------------------------
# read.file()          # mosaic
# with()
# summary()
# glimpse()            # dplyr
# ntiles()             # mosaic
# cut()
# c()
# cbind(); rbind()
# colnames()
# rownames()
# relevel()
# reorder()

## ----highlight=FALSE------------------------------------------------
# rep()
# seq()
# sort()
# rank()

## ----highlight=FALSE------------------------------------------------
# select()             # dplyr
# mutate()             # dplyr
# filter()             # dplyr
# arrange()            # dplyr
# summarise()          # dplyr
# group_by()           # dplyr
# left_join()          # dplyr
# inner_join()         # dplyr

## ----more-hooks,eval=TRUE,echo=FALSE--------------------------------
knitr::opts_chunk$set(
	eval=TRUE, 
  size='small',
	fig.width=4,
	fig.height=1.9,
	fig.align="center",
	out.width=".25\\textwidth",
	out.height=".125\\textwidth",
	tidy=TRUE,
	comment=NA
)

## ----echo=FALSE-----------------------
options(width=40)
options(show.signif.stars=FALSE)

## ----coins,fig.keep="last"------------
rflip(6)
do(2) * rflip(6)
coins <- do(1000)* rflip(6)
tally(~ heads, data=coins)

## -------------------------------------
tally(~ heads, data=coins, format="perc")
tally(~ (heads>=5 | heads<=1) , data=coins)

## ----coins-hist,fig.keep="last"-------
gf_histogram(~ heads, data = coins, binwidth = 1,
            fill = ~ (heads >=5 | heads <= 1))

## ----tally----------------------------
tally(sex ~ substance, data=HELPrct)
mean(age ~ sex, data = HELPrct)
diffmean(age ~ sex, data = HELPrct)
favstats(age ~ sex, data = HELPrct)

## ----densityplot,fig.height=2.4, tidy = FALSE----
gf_dens(~ age | sex, data = HELPrct,
                color = ~ substance) 

## ----bwplot---------------------------
gf_boxplot(age ~ substance | sex, data = HELPrct)

## ----message=FALSE--------------------
pval(binom.test(~ sex, data = HELPrct))
confint(t.test(~ age, data = HELPrct))

## ----tidy=FALSE-----------------------
model <- 
  lm(age ~ sex + substance, data = HELPrct) 
anova(model)

## ----tidy=FALSE-----------------------
gf_point(Sepal.Length ~ Sepal.Width, 
        color = ~Species, data = iris) 

## ----fig.keep="last", tidy=FALSE, fig.height=2.3----
model <- 
  lm(length ~ width + sex, data = KidsFeet)
l.hat <- makeFun(model)
l.hat(width = 8.25, sex = "B")
gf_point(length ~ width, data = KidsFeet,
         color = ~ sex) %>%
  gf_fun(l.hat(w, sex = "B") ~ w, color = ~"B") %>%
  gf_fun(l.hat(w, sex = "G") ~ w, color = ~"G")

## ----fig.height=1.75------------------
gf_dist("chisq", df=4)

## ----include=FALSE--------------------
tally(homeless ~ sex, data = HELPrct)

## ----include=FALSE--------------------
chisq.test(tally(homeless ~ sex, data = HELPrct))
prop.test(homeless ~ sex, data = HELPrct)