# L1c1b : Covariance, correlation

 G02AAF Computes the nearest correlation matrix to a real square matrix, using the method of Qi and Sun G02ABF Computes the nearest correlation matrix to a real square matrix, augmented G02AAF to incorporate weights and bounds G02AEF Computes the nearest correlation matrix with $k$-factor structure to a real square matrix G02AJF Computes the nearest correlation matrix to a real square matrix, using element-wise weighting G02BAF Pearson product-moment correlation coefficients, all variables, no missing values G02BGF Pearson product-moment correlation coefficients, subset of variables, no missing values G02BNF Kendall/Spearman non-parametric rank correlation coefficients, no missing values, overwriting input data G02BQF Kendall/Spearman non-parametric rank correlation coefficients, no missing values, preserving input data G02BTF Update a weighted sum of squares matrix with a new observation G02BUF Computes a weighted sum of squares matrix G02BWF Computes a correlation matrix from a sum of squares matrix G02BXF Computes (optionally weighted) correlation and covariance matrices G02BYF Computes partial correlation/variance-covariance matrix from correlation/variance-covariance matrix computed by G02BXF G02BZF Combines two sums of squares matrices, for use after G02BUF G02HKF Calculates a robust estimation of a correlation matrix, Huber's weight function G02HLF Calculates a robust estimation of a correlation matrix, user-supplied weight function plus derivatives G02HMF Calculates a robust estimation of a correlation matrix, user-supplied weight function

© The Numerical Algorithms Group Ltd, Oxford UK. 2013