AutovarCore generates networks given a data frame. AutovarCore is a simplified/efficient version of Autovar.
To install, type the following:
install.packages('devtools')
devtools::install_github('roqua/autovarCore')
For more information on Autovar, see autovar.nl.
You should use Autovar if you
You should use AutovarCore if you
library('autovarCore')
# AutovarCore requires input data in data.frame format.
# If you have data in a .csv, .dta, or .sav file, use
# the 'foreign' library to load this data into R first.
# (You may need to type:
# install.packages('foreign')
# if you do not have the foreign library installed on
# your system.)
library('foreign')
# This example data set can be downloaded from
# https://autovar.nl/datasets/aug_pp5_da.sav
suppressWarnings(dfile <- read.spss('~/Downloads/aug_pp5_da.sav'))
dframe <- data.frame(Activity = dfile$Activity, Depression = dfile$Depression)
# Call autovar with the given data frame. Type:
# ?autovar
# (after having typed "library('autovarCore')") to see
# which other options are available.
models_found <- autovar(dframe, selected_column_names = c('Activity', 'Depression'))
# Show details for the best model found
print(models_found[[1]])
apply_ln_transformation
assess_joint_sktest
assess_kurtosis
assess_portmanteau
assess_portmanteau_squared
assess_skewness
autovar
autovarCore-package
compete
day_dummies
daypart_dummies
explode_dummies
impute_datamatrix
invalid_mask
model_is_stable
model_score
needs_trend
rcpp_hello_world
residual_outliers
run_tests
run_var
select_valid_masks
selected_columns
trend_columns
validate_params
validate_raw_dataframe