#include <yat/regression/MultiCox.h>

Public Member Functions
	MultiCox (void)
	Default Constructor.

	MultiCox (const MultiCox &other)
	Copy Constructor. More...

	MultiCox (MultiCox &&other)

	~MultiCox (void)

MultiCox &	operator= (const MultiCox &other)

MultiCox &	operator= (MultiCox &&other)

void	add (const utility::VectorBase &x, double time, bool event)
	add a sample More...

void	add (const utility::MatrixBase &x, const utility::VectorBase &time, const std::vector< char > &event)
	Add n data points. More...

void	clear (void)

void	train (void)

double	b (size_t i) const

double	z (size_t i) const

double	p (size_t i) const
	two-sided p-value for the null-hypothesis that is zero.

double	hazard_ratio (size_t i) const

double	hazard_ratio_lower_CI (size_t, double alpha=0.95) const

double	hazard_ratio_upper_CI (size_t, double alpha=0.95) const

const utility::MatrixBase &	covariance (void) const

Detailed Description

Class handling multivariable Cox regression.

The time-dependent hazard is modeled as $\lambda(t|x) = \lambda_0(t) \exp (x * b)$

Model parameters are inferred as described by Breslow (1975) and tied timepoints are handled as suggested by Efron (1975).

Constructor & Destructor Documentation

◆ MultiCox() [1/2]

theplu::yat::regression::MultiCox::MultiCox ( const MultiCox & other )

Copy Constructor.

Create a copy of other and its data

◆ MultiCox() [2/2]

theplu::yat::regression::MultiCox::MultiCox ( MultiCox && other )

Move constructor

◆ ~MultiCox()

theplu::yat::regression::MultiCox::~MultiCox ( void )

Destructor

Member Function Documentation

◆ add() [1/2]

void theplu::yat::regression::MultiCox::add	(	const utility::VectorBase &	x,
		double	time,
		bool	event
	)

add a sample

Parameters

x	value covariate vector for sample
time	timepoint when event occured for sample or sample was censored
event	true if sample was not censored

◆ add() [2/2]

void theplu::yat::regression::MultiCox::add	(	const utility::MatrixBase &	x,
		const utility::VectorBase &	time,
		const std::vector< char > &	event
	)

Add n data points.

Each column in X corresponds to a data point. Equivalent to looping over the columns and vectors and calling single-sample version of add.

◆ b()

double theplu::yat::regression::MultiCox::b ( size_t i ) const

return ith element of the b-vector

◆ clear()

void theplu::yat::regression::MultiCox::clear ( void )

Remove all data

◆ covariance()

const utility::MatrixBase& theplu::yat::regression::MultiCox::covariance ( void ) const

Returns: the covariance of the estimate b-vector; the diagonal contains the standard errors.

◆ hazard_ratio()

double theplu::yat::regression::MultiCox::hazard_ratio ( size_t i ) const

The hazard ratio associated with the ith variable.

◆ hazard_ratio_lower_CI()

double theplu::yat::regression::MultiCox::hazard_ratio_lower_CI	(	size_t	,
		double	alpha = `0.95`
	)		const

Lower bound of confidence interval

◆ hazard_ratio_upper_CI()

double theplu::yat::regression::MultiCox::hazard_ratio_upper_CI	(	size_t	,
		double	alpha = `0.95`
	)		const

Upper bound of confidence interval

◆ operator=() [1/2]

MultiCox& theplu::yat::regression::MultiCox::operator= ( const MultiCox & other )

Assignment operator

◆ operator=() [2/2]

MultiCox& theplu::yat::regression::MultiCox::operator= ( MultiCox && other )

Move assignment

◆ train()

void theplu::yat::regression::MultiCox::train ( void )

Find the parameters of the model

◆ z()

double theplu::yat::regression::MultiCox::z ( size_t i ) const

Returns: ith element of b divided by its standard error.

The documentation for this class was generated from the following file:

yat/regression/MultiCox.h

Public Member Functions