ID_SingleLevelGibbsSampler

Single record of predicted values from Count quantile regressions in a numeric vector form

CountDataLevel

Single record of predicted values from Size quantile regressions in a numeric vector form

SizeDataLevel

The number of periods you set up to forecast

FC_Periods

The number of simulations you want to have run for each period in 1 to FC_Periods

nSims

A numeric vector of the quantiles used for Count modeling

CountList

A numeric vector of the quantiles used for Size modeling

SizeList

ID_SingleLevelGibbsSampler for collapsed gibbs sampler from quantile regressions

Automates and ensures high quality output for most
of your machine learning and data science tasks. The package contains
high quality functions that run at efficient speed with minimal memory
constraints for supervised learning, unsupervised learning, feature
engineering, model evaluation and interpretation, along with some
helper functions for graphing. AutoCatBoostClassifier(),
AutoCatBoostRegression(), and AutoCatBoostMultiClass() have a
dependency to the catboost package which isn't part of the CRAN
repository at the time of this writing. The link to the catboost URL
to download the package for use is in the Additional_repositories
field below, which has the installation instructions. You need to
install that package to make use of the AutoCatBoost_ functions.

ID_SingleLevelGibbsSampler: ID_SingleLevelGibbsSampler for collapsed gibbs sampler

Description

Usage

Arguments

Value

See Also