hmatrix-gsl-stats-0.4.1.3: GSL Statistics interface

Numeric.GSL.Fitting.Linear

Description

GSL linear regression functions

http://www.gnu.org/software/gsl/manual/

Synopsis

Documentation

Arguments

 :: Vector Double x data -> Vector Double y data -> (Double, Double, Double, Double, Double, Double) (c_0,c_1,cov_00,cov_01,cov_11,chi_sq)

fits the model Y = C X

Arguments

 :: Vector Double x data -> Vector Double x weights -> Vector Double y data -> (Double, Double, Double, Double, Double, Double) (c_0,c_1,cov_00,cov_01,cov_11,chi_sq)

fits the model Y = C X, with x data weighted

Arguments

 :: Double x data point -> Double c0 -> Double c1 -> Double cov00 -> Double cov01 -> Double cov11 -> (Double, Double) (y,error)

computes the fitted function and standard deviation at the input point

Arguments

 :: Matrix Double design matrix (X) -> Vector Double observations -> (Vector Double, Matrix Double, Double) (coefficients,covariance,chi_sq)

fit the model Y = C X, with design matrix X | X is a design matrix X_{ij} = x_j(i) with i observations and p predictors | a polynomial would be X_{ij} = x_i^j | a fourier series would be X_{ij} = sin (omega_j x_i)

Arguments

 :: Matrix Double design matrix (X) -> Vector Double weights -> Vector Double observations -> (Vector Double, Matrix Double, Double) (coefficients,covariance,chi_sq)

fit the model Y = C X, with design matrix X, and x weighted

Arguments

 :: Vector Double input point -> Vector Double the coefficients -> Matrix Double the covariance matrix -> (Double, Double) (y,y_error)

computes the fitted function and standard deviation at the input point