TSA Random Sequence Generation VI

Owning Palette: Utilities VIs

Requires: Advanced Signal Processing Toolkit

Generates a pseudorandom univariate or multivariate (vector) time series from different types of distribution. You must manually select the polymorphic instance to use.

Details  Examples

TSA Normal Distribution (Waveform)

	samples specifies the number of samples of the generated time series Xt. The value must be greater than or equal to 0. The default is 1024.
	mean specifies the value of the center of the normal distribution. The default is 0.
	standard deviation specifies the standard deviation value of the normal distribution. The default is 1.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	seed specifies the seed of the noise sample generator. Seeds with different values greater than 0 generate different noise sequences. Values less than 0 cause reseeding each time this VI runs. The default is –1.
	Xt returns the random univariate time series.
	error out contains error information. This output provides standard error out functionality.

TSA Vector Normal Distribution (Waveform)

	samples specifies the number of samples of the generated time series Xt. The value must be greater than or equal to 0. The default is 1024.
	mean specifies the mean values this VI uses to define the center of the multivariate normal distribution.
	covariance specifies the covariance matrix this VI uses to define the multivariate (vector) normal distribution. This matrix must be symmetric.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	Xt returns the random multivariate (vector) time series.
	error out contains error information. This output provides standard error out functionality.

TSA Uniform Distribution (Waveform)

	samples specifies the number of samples of the generated time series Xt. The value must be greater than or equal to 0. The default is 1024.
	lower endpoint specifies the minimum value for the uniform distribution.
	upper endpoint specifies the maximum value for the uniform distribution.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	seed specifies the seed of the noise sample generator. Seeds with different values greater than 0 generate different noise sequences. Values less than 0 cause reseeding each time this VI runs. The default is –1.
	Xt returns the random univariate time series.
	error out contains error information. This output provides standard error out functionality.

TSA Chi-Square Distribution (Waveform)

	samples specifies the number of samples of the generated time series Xt. The value must be greater than or equal to 0. The default is 1024.
	degrees of freedom specifies the degrees of freedom this VI uses to define the chi-square distribution.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	Xt returns the random univariate time series.
	error out contains error information. This output provides standard error out functionality.

TSA T Distribution (Waveform)

	samples specifies the number of samples of the generated time series Xt. The value must be greater than or equal to 0. The default is 1024.
	degrees of freedom specifies the degrees of freedom this VI uses to define the t distribution.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	Xt returns the random univariate time series.
	error out contains error information. This output provides standard error out functionality.

TSA F Distribution (Waveform)

	samples specifies the number of samples of the generated time series Xt. The value must be greater than or equal to 0. The default is 1024.
	numerator degrees of freedom specifies the degrees of freedom of the numerator this VI uses to define the F distribution.
	denominator degrees of freedom specifies the degrees of freedom of the denominator this VI uses to define the F distribution.
	error in describes error conditions that occur before this node runs. This input provides standard error in functionality.
	Xt returns the random univariate time series.
	error out contains error information. This output provides standard error out functionality.

TSA Random Sequence Generation Details

This VI generates a pseudorandom sequence from different distributions, such as the normal, uniform, chi-square, t, and F distributions.

Normal distribution random series

X_t is a univariate time series from the normal distribution. X_t satisfies the following probability density function:

where m is mean, and s is standard deviation.

X_t is a multivariate (vector) random series with m channels from the joint normal distribution. X_t satisfies the following probability density function:

where m is mean, S is the m×m covariance matrix, and X^T is the transpose vector of X.

Uniform distribution random series

X_t is a random univariate time series from the uniform distribution. X_t satisfies the following probability density function:

where a is lower endpoint, and b is upper endpoint.

Chi-square distribution random series

X_t is a random univariate time series from the chi-square distribution. X_t satisfies the probability density function f(X_t) as

where n is degrees of freedom, and G(x) is a gamma function defined as

T distribution random series

X_t is a random univariate time series from the t distribution. X_t satisfies the following probability density function:

where n is degrees of freedom.

F distribution random series

X_t is a random univariate time series from the F distribution. X_t satisfies the following probability density function:

where n₁ is numerator degrees of freedom, and n₂ is denominator degrees of freedom.

This VI computes the F distribution by dividing each independent chi-square distribution by n₁ and n₂ respectively, then calculating the ratio of the two divided chi-square distributions.

Examples

Refer to the following VIs for examples of using the TSA Random Sequence Generation VI:

• Random Series Generate VI: labview\examples\Time Series Analysis\TSAGettingStarted
• Series Statistical Analysis VI: labview\examples\Time Series Analysis\TSAGettingStarted