knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.path = "man/figures/README-", out.width = "100%" )
The goal of gamlssutils is to provide functions to ease extracting and displaying output from GAMLSS models.
You can install the development version from GitHub with:
# install.packages("devtools") devtools::install_github("MiguelRodo/gamlssutils")
Here we load the package and create example data:
library(gamlssutils) set.seed(1) data_mod <- data.frame(x = rnorm(20, 5) + rgamma(20, 0.01, 0.0001)) data_mod[['y']] <- 3 * data_mod[['x']] + rnorm(20, sd = 5) head(data_mod)
You can easily extract coefficients from all parameters into an organised table:
mod <- gamlss::gamlss(formula = y ~ -1 + x, family = "BCPE", data = data_mod, control = gamlss::gamlss.control(trace = FALSE)) get_coef_tbl(mod = mod)
These tables are pleasantly displayed with pander::pandoc.table
(remember to set results = 'asis'
in chunk options):
# install.packages('pander') pander::pandoc.table(get_coef_tbl(mod = mod))
You can get the LR test results neatly put into a table:
# data set.seed(1) data_mod <- data.frame(x = rnorm(20, 5) + rgamma(20, 0.01, 0.0001)) data_mod[['y']] <- 3 * data_mod[['x']] + rnorm(20, sd = 5) # models mod_mu <- gamlss::gamlss(formula = y ~ -1 + x, family = "NO", data = data_mod, control = gamlss::gamlss.control(trace = FALSE)) mod_sigma <- gamlss::gamlss(formula = y ~ -1 + x, sigma.formula = ~ x, family = "NO", data = data_mod, control = gamlss::gamlss.control(trace = FALSE)) # table lr_tbl <- get_lr_tbl(mod = mod_sigma, mod_null = mod_mu, mod_null_name = "sigma") pander::pandoc.table(lr_tbl)
The \code{vcov.gamlss} function (i.e. the \code{vcov}) method for \code{gamlss} objects) expects to find the object passed to the \code{data} parameter in the call to \code{gamlss} to be found in the global environment. However, this may often not be the case, as that object may have changed or else may longer/may have never existed in the global environment. The function get_vcov
gets around it. You pass it the dataframe that was given to the \code{gamlss} function and the name it had at the time (as a string), and get_vcov
will then be able to calculate the variance-covariance matrix in any environment.
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