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Owning Palette: Time Series Analysis VIs

Installed With: Advanced Signal Processing Toolkit. This topic might not match its corresponding palette in LabVIEW depending on your operating system, licensed product(s), and target.

Use the Statistical Analysis VIs to compute the following statistical parameters of a univariate or multivariate (vector) time series: mean, deviation and variance, skewness and kurtosis, entropy, covariance, confidence limit, normal distribution, whiteness, and stationarity. You also can use the Statistical Analysis VIs to perform independent component analysis and principal component analysis on multivariate time series.

The VIs on this palette can return general LabVIEW error codes or specific time series analysis error codes.

Palette Object	Description
TSA Confidence Limits	Computes confidence limits of the mean and standard deviation values of the input univariate or multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Covariance	Computes the covariance matrix or correlation matrix of an input multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Deviation and Variance	Computes the standard deviation, variance, and coefficients of variation values of an input univariate or multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Entropy	Computes the entropy of an input univariate or multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Independent Component Analysis	Performs independent component analysis (ICA) on an input multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Mean	Computes the mean values of an input univariate or multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Normal Distribution Test	Determines if an input univariate time series is normally distributed by comparing the discrete histogram of the time series with the assumed normal distribution histogram that this VI generates according to the mean and variance values of the time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Principal Component Analysis	Performs principal component analysis (PCA) on an input multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Skewness and Kurtosis	Computes the skewness and kurtosis values of an input univariate or multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Stationarity Test	Estimates the stationarity of an input univariate time series by examining the mean and variance values of the subsequences. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA Whiteness Test	Estimates the randomness of an input univariate time series and plots the correlogram. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.

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