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tsmethods (version 1.0.2)

Time Series Methods

Description

Generic methods for use in a time series probabilistic framework, allowing for a common calling convention across packages. Additional methods for time series prediction ensembles and probabilistic plotting of predictions is included. A more detailed description is available at which shows the currently implemented methods in the 'tsmodels' framework.

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Install

install.packages('tsmethods')

Monthly Downloads

712

Version

1.0.2

License

GPL-2

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Maintainer

Alexios Ghalanos

Last Published

September 22nd, 2024

Functions in tsmethods (1.0.2)

tscokurt

Co-Kurtosis
tsdecompose

Time Series Model Decomposition
tsmoments

Analytic Moments
tsprofile

Profile a time series model
tsequation

Model Equation Extractor
tscov

Covariance matrix.
tsensemble.ensemble.spec

Ensembles predictions using their posterior predictive or simulated distribution
tsfilter

Online Time Series Filter
tsdiagnose

Extract diagnostic model information
tsgrowth.tsmodel.predict

Growth Calculation
tsspec

Extract specification object from estimation object
tsreport

Report Method
tsmethods-package

tsmethods: Time Series Methods
tsmetrics

Time Series Performance Metrics Method
unconditional

Unconditional Value
estimate

Model Estimation
ensemble_modelspec

Ensemble specification
tsbenchmark

Time Series Model Benchmarking
halflife

Half Life
tsaggregate

Time Series Aggregation
pit

Probability Integral Transform (PIT)
distribution_list

Multiple Distributions
tsbacktest

Time Series Model Backtesting
estimate_ad

Estimation method using AD
plot.tsmodel.distribution

Plots of predictive distributions
tscoskew

Co-Skewness
tsconvert.tsmodel.distribution

Convert a distribution object to a long form data.table
tsconvolve

Convolution of Distributions
tsconvert

Conversion method from one object to another
tscor

Correlation matrix.
tscalibrate

Prediction Calibration method