naginterfaces.library.correg.linregm_​obs_​edit

naginterfaces.library.correg.linregm_obs_edit(update, isx, q, x, ix, y, rss, mean='M', wt=None)[source]

linregm_obs_edit adds or deletes an observation from a general regression model fitted by linregm_fit().

For full information please refer to the NAG Library document for g02dc

https://support.nag.com/numeric/nl/nagdoc_30.2/flhtml/g02/g02dcf.html

Parameters
updatestr, length 1

Indicates if an observation is to be added or deleted.

The observation is added.

The observation is deleted.

isxint, array-like, shape

If is greater than , the value contained in is to be included as a value of , for .

qfloat, array-like, shape

Must be array as output by linregm_fit(), linregm_var_add(), linregm_var_del() or linregm_fit_onestep(), or a previous call to linregm_obs_edit.

xfloat, array-like, shape

The values for the dependent variables of the new observation, . The positions will depend on the value of .

ixint

The increment for elements of . Two situations are common:

The values of are to be chosen from consecutive locations in , i.e., .

The values of are to be chosen from a row of a two-dimensional array with first dimension , i.e., .

yfloat

The value of the dependent variable for the new observation, .

rssfloat

The value of the residual sums of squares for the original set of observations.

meanstr, length 1, optional

Indicates if a mean has been used in the model.

A mean term or intercept will have been included in the model by linregm_fit().

A model with no mean term or intercept will have been fitted by linregm_fit().

wtNone or float, optional

If provided, must contain the weight to be used with the new observation.

If is None, the observation is not included in the model.

Returns
qfloat, ndarray, shape

The first elements of the first column of will contain the upper triangular part of columns to will contain the remainder is unchanged.

rssfloat

The updated values of the residual sums of squares.

Note: this will only be valid if the model is of full rank.

Raises
NagValueError
(errno )

On entry, elements of instead of (for mean) .

(errno )

On entry, .

Constraint: .

(errno )

On entry, elements of instead of .

(errno )

On entry, .

Constraint: or .

(errno )

On entry, .

Constraint: .

(errno )

On entry, .

Constraint: or .

(errno )

On entry, .

Constraint: or .

(errno )

On entry, .

Constraint: .

(errno )

On entry, .

Constraint: .

(errno )

The matrix could not be updated.

(errno )

The residual sums of squares cannot be updated.

Notes

In the NAG Library the traditional C interface for this routine uses a different algorithmic base. Please contact NAG if you have any questions about compatibility.

linregm_fit() fits a general linear regression model to a dataset. You may wish to change the model by either adding or deleting an observation from the dataset. linregm_obs_edit takes the results from linregm_fit() and makes the required changes to the vector and the upper triangular matrix produced by linregm_fit(). The regression coefficients, standard errors and the variance-covariance matrix of the regression coefficients can be obtained from linregm_update() after all required changes to the dataset have been made.

linregm_fit() performs a decomposition on the (weighted) matrix of independent variables. To add a new observation to a model with parameters, the upper triangular matrix and vector (the first elements of ) are augmented by the new observation on independent variables in and dependent variable . Givens rotations are then used to restore the upper triangular form.

Note: only and the upper part of are updated the remainder of the matrix is unchanged.

References

Golub, G H and Van Loan, C F, 1996, Matrix Computations, (3rd Edition), Johns Hopkins University Press, Baltimore

Hammarling, S, 1985, The singular value decomposition in multivariate statistics, SIGNUM Newsl. (20(3)), 2–25