scisalt.scipy.LinLsqFit¶

class scisalt.scipy.LinLsqFit(y_unweighted, X_unweighted, y_error=None)[source]¶

Gets the linear least squares for $\beta$ of a problem given $X_{ij} \beta_{i} = y_j$ .

As input, it takes y_unweighted as the measured $y$ , X_unweighted for $X$ , and y_error as the measurement error on $y$ .

Attributes

`X`	The $X$ weighted properly by the errors from y_error
`X_unweighted`	The $X$ .
`beta`	The result $\beta$ of the linear least squares
`chisq_red`	The reduced chi-square of the linear least squares
`covar`	The covariance matrix for the result $\beta$
`y`	The $X$ weighted properly by the errors from y_error
`y_error`	The measured error of $y$ of the problem $X_{ij} \beta_{i} = y_j$ .
`y_fit`	Using the result of the linear least squares, the result of $X_{ij}\beta_i$
`y_unweighted`	The $y$ of the problem $X_{ij} \beta_{i} = y_j$ .