#-----BUILD SCRIPT--------------------------------------------------------------
#-----Generate documentation----------------------------------------------------
roxygen2::roxygenise()
#-----Create website for package------------------------------------------------
pkgdown::build_site()
#-----Build package-------------------------------------------------------------
# piecewiseSEM <- devtools::as.package("./piecewiseSEM")
# Add files to .Rbuildignore
usethis::use_build_ignore(c("build.R", ".git", ".gitignore", "docs"))
# Load package
devtools::load_all(".", reset = T)
# Check and build
devtools::check(".", cran = T)
devtools::build(".")
devtools::check_built(".")
# Check on R-hub
# devtools::spell_check()
# devtools::check_rhub("piecewiseSEM")
# check_win_devel()
#-----Examples------------------------------------------------------------------
#run_examples(piecewiseSEM)
library(piecewiseSEM)
data(keeley)
# fit model
mod <- psem(
lm(rich ~ cover, data=keeley),
lm(cover ~ firesev, data=keeley),
lm(firesev ~ age, data=keeley),
data = keeley)
mod
# d-sep tests
basisSet(mod)
dSep(mod)
fisherC(mod)
AIC(mod) #likelihood based
AIC(mod, AIC.type = "dsep") #dsep based
# Chisq
LLchisq(mod)
AIC(mod, AIC.type = "loglik")
# Rsquared
rsquared(mod)
# get summary
summary(mod)
# get residuals
residuals(mod)
# plotting
# plot(mod)
#
# plot(mod, node_attrs = list(
# shape = "rectangle", color = "black",
# fillcolor = "orange", x = 3, y = 1:4))
# add correlated error
mod2 <- psem(
lm(rich ~ cover, data=keeley),
lm(cover ~ firesev + age, data=keeley),
lm(firesev ~ age, data=keeley),
rich %~~% firesev,
data = keeley)
# get summary
summary(mod2)
# AIC of two models
anova(mod, mod2)
# test mixed models
library(lme4)
# library(MASS)
library(nlme)
# using lme
shipley_psem <- psem(
lme(DD ~ lat, random = ~ 1 | site / tree, na.action = na.omit,
data = shipley),
lme(Date ~ DD, random = ~ 1 | site / tree, na.action = na.omit,
data = shipley),
lme(Growth ~ Date, random = ~ 1 | site / tree, na.action = na.omit,
data = shipley),
glmer(Live ~ Growth + (1 | site) + (1 | tree),
family = binomial(link = "logit"), data = shipley))
summary(shipley_psem)
# using lme4
shipley_psem_lme4 <- psem(
lmer(DD ~ lat + (1 | site / tree),
data = shipley),
lmer(Date ~ DD + (1 | site / tree),
data = shipley),
lmer(Growth ~ Date + (1 | site / tree),
data = shipley),
glmer(Live ~ Growth + (1 | site) + (1 | tree),
family = binomial(link = "logit"), data = shipley),
data = shipley)
summary(shipley_psem_lme4)
# multigroup
data(meadows)
meadows$grazed <- factor(meadows$grazed)
meadow_mod <- psem(
lm(mass ~ elev, data = meadows),
lm(rich ~ elev + mass, data = meadows),
data = meadows
)
multigroup(meadow_mod, group = "grazed")
#-----Submit to CRAN------------------------------------------------------------
devtools::release(".")
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