glasso_gain_function: Closure generating function to calculate gains when splitting...
In mlondschien/hdcd: High - Dimensional Change Point Detection

Closure generating function to calculate gains when splitting and learning a glasso model

1	glasso_gain_function(x, start, end, lambda, control = hdcd_control())

`x`	A matrix with observations in rows
`start`	The start of the investigated interval
`end`	The end of the investigated interval
`lambda`	Tuning parameter passed to the method.
`control`	an object of type `hdcd_control` returned by hdcd_control

A closure with parameters x, start and end, that when evaluated will itself return a closure with parameter split_point. This calculates the gain when splitting the segment (start, end] of x at split_point. If the closure is additionally supplied with evaluate_all = TRUE, an array of length nrow(x) is returned with differences of loglikelihoods for each observation in (start, end] when split at split_point. Glasso Gain Function

A closure with parameters x, start and end, that when evaluated will itself return a closure with arguments split_point and split_candidates. Evaluated this function returns the gain when splitting the segment (start, end] of x at split_point.