ivs.statistics.linearregression.PolynomialModel

Class PolynomialModel

Class to implement a polynomial model

The class implements a polynomial model function of the form

y(x) = a_0 * a_1 * x + a_2 * x^2 + ...

where y are the responses (observables), x are the covariates, the a_i are the regression coefficients (to be determined). Such a class provides convenient way of creating a polynomial model.

Remarks:

PolynomialModel instances can be added to other PolynomialModel or LinearModel instances to give a new LinearModel instance.

Properties

[hide private]

Inherited from object: __class__

init(self, covariate, covariateName, orderList, covMatrix=None)
(Constructor)

source code

Initialiser of the PolynomialModel class.

Example:

>>> time = linspace(0,10,100)
>>> pm = PolynomialModel(time, "t", [2,1])

Parameters:

covariate (ndarray) - an array of size N with the covariate values, where N is the number of observations
covariateName (string) - the (preferably short) name of the covariate. E.g. "t", or "x".
orderList (list) - list of the orders that should be included in the model. E.g. [3,0,1] implies the model a_0 * x^3 + a_1 + a_2 * x
covMatrix (ndarray) - square array containing the covariance matrix of the observations. This way, weights and correlations can be taken into account.

Returns: PolynomialModel

an instance of PolynomialModel, subclass of LinearModel

Overrides: object.__init__

Class PolynomialModel

__init__(self, covariate, covariateName, orderList, covMatrix=None) (Constructor)

init(self, covariate, covariateName, orderList, covMatrix=None)
(Constructor)