# Statistical Analysis VIs

LabVIEW 2014 Advanced Signal Processing Toolkit Help

Edition Date: June 2014

Part Number: 372656C-01

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Owning Palette: Time Series Analysis VIs

Requires: 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 ObjectDescription
TSA Confidence LimitsComputes confidence limits of the mean and standard deviation values of the 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 CovarianceComputes the covariance matrix or correlation matrix of a 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 VarianceComputes the standard deviation, variance, and coefficients of variation values of a 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 EntropyComputes the entropy of a 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 AnalysisPerforms independent component analysis (ICA) on a multivariate (vector) time series. Wire data to the Xt input to determine the polymorphic instance to use or manually select the instance.
TSA MeanComputes the mean values of a 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 TestDetermines if a 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 AnalysisPerforms principal component analysis (PCA) on a 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 KurtosisComputes the skewness and kurtosis values of a 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 TestEstimates the stationarity of a 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 TestEstimates the randomness of a 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.