FamModelFit: Abstract class for results of a fitted 'FamModel' model

In kinnamon-lab/FamModel: Regression Modeling for Family-Based Genetic Studies

Description

An abstract R6 class defining the pattern for all FamModelFit subclasses created by fitting a model to a FamData object using one of its model-fitting methods. This class provides only a default constructor without any initializer.

Methods

Public methods

• FamModelFit$get_data()

• FamModelFit$get_optres()

• FamModelFit$get_theta_hat()

• FamModelFit$get_V_theta_hat()

• FamModelFit$print()

• FamModelFit$contrast()

• FamModelFit$clone()

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Method get_data()

Returns the FamData object that produced this model fit.

Usage

FamModelFit$get_data()

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Method get_optres()

Returns list of optimization results.

Usage

FamModelFit$get_optres()

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Method get_theta_hat()

Returns \hat{θ}, the numeric vector of parameter estimates.

Usage

FamModelFit$get_theta_hat()

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Method get_V_theta_hat()

Returns the numeric matrix \hat{V}(\hat{θ}), the estimated covariance matrix of the parameter estimates.

Usage

FamModelFit$get_V_theta_hat()

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Method print()

Formatted printing of the FamModelFit object.

Usage

FamModelFit$print(...)

Arguments

...

Arguments passed on to print_ests().

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Method contrast()

Create a new Contrast object.

Usage

FamModelFit$contrast(L_mat, m)

Arguments

L_mat

A contrast vector (1 df) or matrix (>1 df) containing one contrast in each row. The contrast vector must have a number of elements equal to the number of model parameters. The contrast matrix must be of full row rank and have a number of columns equal the number of model parameters.

m

An optional vector containing the null value for each contrast. Will be set to the zero vector of length nrow(L_mat) if not specified.

Returns

A Contrast object for the specified arguments and this model fit.

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Method clone()

The objects of this class are cloneable with this method.

Usage

FamModelFit$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

kinnamon-lab/FamModel documentation built on April 26, 2021, 4:38 a.m.