multivariate: Efficient Logarithmic Discrete Multivariate Likelihood...
In segmentr: Segment Data With Maximum Likelihood

Description Usage Arguments Details Value

Estimate the likelihood of a given segment using the discrete multivariate estimation, implemented efficiently in C++

1 2	multivariate(data, na_action = function(d) d[, colSums(is.na(d)) == 0, drop = FALSE])

`data`	Matrix to estimate the multivariate of. Each row is considered to be an observation, and each column is considered to be a different variable.
`na_action`	A function that is applied to the `data` parameter. Defaults to removing columns with NA.

Calculates the discrete log likelihood multivariate estimation of a data matrix using an algorithm implemented in C++ for performance. This is intended to be used in conjunction with segment(), as the log likelihood function is executed multiple times, which makes it the bottleneck of the computation. Because the multivariate is so commonly used, this efficient implementation is provided.

the estimate of the Discrete Maximum Likelihood for the dataframe provided.

segmentr documentation built on Aug. 29, 2019, 1:03 a.m.