StatLS: Difference between revisions
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(Created page with "==Purpose== Compute parameter statistics for least squares problems. ==Calling Syntax== <pre> LS = StatLS(x_k, r_k, J_k); </pre> ==Inputs== {| class="wikitable" !Input||Des...") |
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[[Category:Utility Functions]] | |||
==Purpose== | ==Purpose== | ||
Latest revision as of 10:55, 22 July 2011
Purpose
Compute parameter statistics for least squares problems.
Calling Syntax
LS = StatLS(x_k, r_k, J_k);
Inputs
Input | Description |
---|---|
x_k | Optimal parameter vector, length n. |
r_k | Residual vector, length m. |
J_k | Jacobian matrix, length m by n. |
Outputs
Structure LS with fields:
Output | Description |
---|---|
SSQ | Sum of squares: r'k * rk |
covar | Covariance matrix: Inverse of J' * diag(1./(r'k * rk )) * J |
sigma2 | Estimate squared standard deviation of problem, SSQ / Degrees of freedom, i.e. SSQ/(m-n) |
Corr | Correlation matrix: Normalized Covariance matrix |
Cov./(CovDiag * CovDiag'), where CovDiag = sqrt(diag(Cov)) | |
StdDev | Estimated standard deviation in parameters: CovDiag * sqrt(sigma2) |
x | =x_k, the input x |
ConfLim | 95 % Confidence limit (roughly) assuming normal distribution of errors ConfLim = 2 * LS.StdDev |
CoeffVar | The coefficients of variation of estimates: StdDev./xk |