Time Series Analysis

Analyze time series data by identifying linear and nonlinear models, including AR, ARMA, and state-space models; forecast values


ar Estimate parameters of AR model for scalar time series
armax Estimate parameters of ARMAX model using time-domain data
arx Estimate parameters of ARX or AR model using least squares
etfe Estimate empirical transfer functions and periodograms
spa Estimate frequency response with fixed frequency resolution using spectral analysis
spafdr Estimate frequency response and spectrum using spectral analysis with frequency-dependent resolution
ivar AR model estimation using instrumental variable method
n4sid Estimate state-space model using subspace method
ssest Estimate state-space model using time or frequency domain data
pem Prediction error estimate for linear and nonlinear model
nlarx Estimate parameters of nonlinear ARX model
idpoly Polynomial model with identifiable parameters
idss State-space model with identifiable parameters
idnlarx Nonlinear ARX model
getpvec Model parameters and associated uncertainty data
setpvec Modify value of model parameters
init Set or randomize initial parameter values
noise2meas Noise component of model
spectrum Output power spectrum of time series models
forecast Forecast identified model output
sim Simulate response of identified model
arOptions Option set for ar
forecastOptions Option set for forecast
simOptions Option set for sim

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