LICORS: estimate_state_probs – R documentation

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estimate_state_probs

Estimate conditional/marginal state probabilities

Description

Estimates P(S = s_k; \mathbf{W}), k = 1, …, K, the probability of being in state s_k using the weight matrix \mathbf{W}.

These probabilites can be marginal (P(S = s_k; \mathbf{W})) or conditional (P(S = s_k \mid \ell^{-}, \ell^{+}; \mathbf{W})), depending on the provided information (pdfs$PLC and pdfs$FLC).

If both are NULL then estimate_state_probs returns a vector of length K with marginal probabilities.
If either of them is not NULL then it returns an N \times K matrix, where row i is the probability mass function of PLC i being in state s_k, k = 1, …, K.

Usage

estimate_state_probs(weight.matrix = NULL, states = NULL, pdfs = list(FLC = NULL, 
    PLC = NULL), num.states = NULL)

Arguments

`weight.matrix`	N \times K weight matrix
`states`	vector of length N with entry i being the label k = 1, …, K of PLC i
`pdfs`	a list with estimated pdfs for PLC and/or FLC evaluated at each PLC, i=1, …, N and/or FLC, i=1, …, N
`num.states`	number of states in total. If `NULL` (default) then it sets it to `max(states)` or `ncol(weight.matrix)` - depending on which one is provided.

Value

A vector of length K or a N \times K matrix.

Examples

WW <- matrix(runif(10000), ncol = 10)
WW <- normalize(WW)
estimate_state_probs(WW)

LICORS

Light Cone Reconstruction of States - Predictive State Estimation From Spatio-Temporal Data

v0.2.0

GPL-2

Authors

Georg M. Goerg <gmg@stat.cmu.edu>

Initial release

2013-11-20