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dse (version 2020.2-1)

Dynamic Systems Estimation (Time Series Package)

Description

Tools for multivariate, linear, time-invariant, time series models. This includes ARMA and state-space representations, and methods for converting between them. It also includes simulation methods and several estimation functions. The package has functions for looking at model roots, stability, and forecasts at different horizons. The ARMA model representation is general, so that VAR, VARX, ARIMA, ARMAX, ARIMAX can all be considered to be special cases. Kalman filter and smoother estimates can be obtained from the state space model, and state-space model reduction techniques are implemented. An introduction and User's Guide is available in a vignette.

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Version

Install

install.packages('dse')

Monthly Downloads

337

Version

2020.2-1

License

GPL-2

Maintainer

Paul Gilbert

Last Published

February 26th, 2020

Functions in dse (2020.2-1)

Riccati Equation

extractforecastCov

Extract Forecast Covariance

Calculate Portmanteau statistic

Time Series Models

Estimate a TSmodel

time series data object

checkConsistentDimensions

Check Consistent Dimensions

Calculate the acf for an object

checkBalanceMittnik

Check Balance of a TSmodel

featherForecasts

Multiple Horizon-Step Ahead Forecasts

State Space Models

combine.forecastCov

Combine 2 Forecast Cov Objects

forecastCovEstimatorsWRTdata

Calculate Forecast Cov of Estimators WRT Data

is.forecastCovEstimatorsWRTdata.subsets

Check Inheritance

TSdata.forecastCov

TS Extractor Specific Methods

Estimate a TSmodel

Estimated Time Series Model

forecastCovCompiled

Forecast covariance for different models - internal

Construct TSdata time series object

Evaluate an ARMA TSmodel

Autocorrelations Diagnostics

Add Model Roots to a plot

Combine two objects.

Estimate a TSmodel

Balance a state space model

Check Balance of a TSmodel

Select Best Model

Dynamic Systems Estimation - Multivariate Time Series Package

nseries.featherForecasts

Number of Series

Number of Series in in Input or Output

Extract or set Model Parameters

Estimate a TSmodel

Estimate a State Space Model

Fix TSmodel Coefficients (Parameters) to Constants

shockDecomposition

Shock Decomposition

Estimate a state space TSmodel using VAR estimation

residuals.TSestModel

Calculate the residuals for an object

Calculate Model Roots

Simulate a TSmodel

Combine series from two TSdata objects.

Maximum Likelihood Estimation

Estimate a TSmodel

estimatorsHorizonForecastsWRTdata

Estimate models and forecast at given horizons

Set SS Model F Matrix to Constants

horizonForecasts

Calculate forecasts at specified horizons

Evaluate a smoother with a TSmodel

Estimate a VAR TSmodel

tfplot.forecast

Specific Methods for tfplot

Basis Transformation of a Model.

Calculate Stability of a TSmodel

Estimate a VAR TSmodel

tfplot.forecastCov

Plots of Forecast Variance

Four Time Series used in Gilbert (1993)

forecastCovEstimatorsWRTtrue

Compare Forecasts Cov Relative to True Model Output

Weighted Estimation

Evaluate a state space TSmodel

forecastCovWRTtrue

Compare Forecasts to True Model Output

Evaluate a TSmodel

minimumStartupLag

Starting Periods Required

forecastCovReductionsWRTtrue

Forecast covariance for different models

Estimate Models

Minimum Forecast Cov Models

egJofF.1dec93.data

Eleven Time Series used in Gilbert (1995)

Plot Model Roots

informationTests

Tabulates selection criteria

excludeForecastCov

Filter Object to Remove Forecasts

State Dimension of a State Space Model

horizonForecastsCompiled

Calculate forecasts at specified horizons

Extract Forecasts

Print Specific Methods

informationTestsCalculations

Calculate selection criteria

print.forecastCov

Print Specific Methods

print.TSestModel

Display TSmodel Arrays

Forecast Multiple Steps Ahead

Generate a random time series

Calculate Model Observability Matrix

Forecast covariance for different models

Markov Parameters

Specific Methods for tframed Data

setTSmodelParameters

Set TSmodel Parameter Information

Tfplot Specific Methods

Set TSmodel Array Information

roots.estimatedModels

Roots Specific Methods

testEqual.forecast

Specific Methods for Testing Equality

Convert to State Space Innovations Model

Convert to Oform

Scale Methods for TS objects

seriesNamesInput

TSdata Series Names

Select a Data Subset and Model

seriesNamesInput.forecast

TS Input and Output Specific Methods

Calculate Phase Plots

Convert to an ARMA Model

Specific Methods for Testing Equality

summary.forecastCov

Summary Specific Methods

outOfSample.forecastCovEstimatorsWRTdata

Calculate Out-of-Sample Forecasts

Specific Methods for tframed Data

percentChange.TSdata

Calculate percent change

totalForecastCov

Sum covariance of forecasts across all series

Calculate Model Reachability Matrix

Calculate Residuals Statistics and Likelihood

Convert to State Space Model

Convert to Non-Innovation State Space Model

seriesNames.TSdata

Series Names Specific Methods

selectForecastCov

Select Forecast Covariances Meeting Criteria

Specific Methods for Summary

Calculate sum of squared prediction errors

Print Version Information

Dynamic Systems Estimation - Multivariate Time Series Package

Flags to Indicate Use of Compiled Code

Polynomial Utilities

MittnikReduction

Balance and Reduce a Model

ARMA Model Constructor

MittnikReducedModels

Reduced Models via Mittnik SVD balancing

Calculate McMillan Degree