Math

Ø  chi2inv()

A chi-square inverse cumulative distribution function

Ø  cov()

Calculate the covariance between two vectors

Ø  covm()

Calculate the covariance matrix for a matrix

Ø  dism()

Calculate Mahalanobis distance between two vectors on covariance matrix

Ø  elasticnet()

Build models and perform predictions using the elastic net regression method

Ø  eye()

Create a matrix whose major diagonal element is 1 and other elements are 0

Ø  finv()

An inverse cumulative distribution function F

Ø  lasso()

Build models and perform predictions using the Lasso regression method

Ø  mcumsum()

Perform cumulative sum on a matrix or a multidimensional matrix

Ø  mfind()

Search for positions of non-zero members in a vector or matrix

Ø  mmean()

Calculate the mean value within a matrix or a multidimensional marix 

Ø  mnorm()

Normalize a matrix or a multidimensional matrix

Ø  mstd()

Calculate the standard deviation on a matrix or a multidimensional marix

Ø  msum()

Calculate sum on a matrix or a multidimensional marix

Ø  norminv()

An inverse normal distribution function

Ø  ones()

Create a multidimensional matrix where all the elements are1

Ø  pca()

Perform PCA on a matrix and return data for dimensionality reduction

Ø  pls()

Fit together matrices using PLS technique

Ø  ridge()

Build models and perform predictions using the ridge regression method

Ø  sg()

Perform SG smoothing on each row of a vector or a matrix

Ø  tinv()

T inverse cumulative distribution function

Ø  zeros()

Create a multidimensional matrix where all the elements are zero