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predtoolsTS (version 0.1.1)

Time Series Prediction Tools

Description

Makes the time series prediction easier by automatizing this process using four main functions: prep(), modl(), pred() and postp(). Features different preprocessing methods to homogenize variance and to remove trend and seasonality. Also has the potential to bring together different predictive models to make comparatives. Features ARIMA and Data Mining Regression models (using caret).

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Install

install.packages('predtoolsTS')

Monthly Downloads

141

Version

0.1.1

License

GPL (>= 2)

Issues

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Maintainer

Alberto Moreno

Last Published

April 29th, 2018

Functions in predtoolsTS (0.1.1)

modl.arima

Automatic ARIMA model
postp.detrend.differencing

Undo detrend(differencing)
print.prep

Generic function
modl.trControl

Control the splitting to train the data
modl.dataMining

Train the data
plot.prep

Generic function
pred

Predictions
postp.homogenize.log

Undo logarithmic transformation
modl.tsToDataFrame

Ts to data frame transformation
prep.detrend.differencing

Detrend with differencing method
summary.prep

Generic function
prep.deseason.differencing

Deseason with differencing method
postp

Post-processing of pre-processed data
pred.dataMining

Predicts for data mining methods
plot.pred

Generic function
prep

Automatic pre-preprocessing
print.modl

Generic function
prep.homogenize.log

Logarithmic transformation
prep.check.acf

Autocorrelation function
prep.check.adf

Augmented Dickey-Fuller test
prep.detrend.sfsm

Detrend with "substracting full-season means" method
prep.homogenize.boxcox

Box-Cox transformation
modl

Building predictive models
postp.deseason.differencing

Undo deseason(differencing)
pred.arima

Predicts for ARIMA
pred.compareModels

Compare different predictions
print.pred

Generic function
summary.modl

Generic function
summary.pred

Generic function
postp.detrend.sfsm

Undo detrend(substracting full-means method)
postp.homogenize.boxcox

Undo Box-Cox transformation