Description Fields Methods See Also

StatMixRHLP contains all the statistics associated to a MixRHLP model, in particular the E-Step (and C-Step) of the (C)EM algorithm.

`pi_jkr`

Array of size

*(nm, R, K)*representing the logistic proportion for cluster k.`tau_ik`

Matrix of size

*(n, K)*giving the posterior probabilities (fuzzy segmentation matrix) that the curve*y_{i}*originates from the*k*-th RHLP model.`z_ik`

Hard segmentation logical matrix of dimension

*(n, K)*obtained by the Maximum a posteriori (MAP) rule:*z_ik = 1 if z_i = arg max_k tau_ik; 0 otherwise*.`klas`

Column matrix of the labels issued from

`z_ik`

. Its elements are*klas[i] = z_i*,*i = 1,…,n*.`gamma_ijkr`

Array of size

*(nm, R, K)*giving the posterior probabilities that the observation*y_{ij}*originates from the*r*-th regime of the*k*-th RHLP model.`polynomials`

Array of size

*(m, R, K)*giving the values of the estimated polynomial regression components.`weighted_polynomials`

Array of size

*(m, R, K)*giving the values of the estimated polynomial regression components weighted by the prior probabilities`pi_jkr`

.`Ey`

Matrix of size

*(m, K)*.`Ey`

is the curve expectation (estimated signal): sum of the polynomial components weighted by the logistic probabilities`pi_jkr`

.`loglik`

Numeric. Observed-data log-likelihood of the MixRHLP model.

`com_loglik`

Numeric. Complete-data log-likelihood of the MixRHLP model.

`stored_loglik`

Numeric vector. Stored values of the log-likelihood at each EM iteration.

`stored_com_loglik`

Numeric vector. Stored values of the Complete log-likelihood at each EM iteration.

`BIC`

Numeric. Value of BIC (Bayesian Information Criterion).

`ICL`

Numeric. Value of ICL (Integrated Completed Likelihood).

`AIC`

Numeric. Value of AIC (Akaike Information Criterion).

`log_fk_yij`

Matrix of size

*(n, K)*giving the values of the probability density function*f(y_{i} | z_i = k, x, Ψ)*,*i = 1,…,n*.`log_alphak_fk_yij`

Matrix of size

*(n, K)*giving the values of the logarithm of the joint probability density function*f(y_{i}, z_{i} = k | x, Ψ)*,*i = 1,…,n*.`log_gamma_ijkr`

Array of size

*(nm, R, K)*giving the logarithm of`gamma_ijkr`

.

`computeStats(paramMixRHLP)`

Method used in the EM algorithm to compute statistics based on parameters provided by the object

`paramMixRHLP`

of class ParamMixRHLP.`CStep(reg_irls)`

Method used in the CEM algorithm to update statistics.

`EStep(paramMixRHLP)`

Method used in the EM algorithm to update statistics based on parameters provided by the object

`paramMixRHLP`

of class ParamMixRHLP (prior and posterior probabilities).`MAP()`

MAP calculates values of the fields

`z_ik`

and`klas`

by applying the Maximum A Posteriori Bayes allocation rule.*z_ik = 1 if z_i = arg max_k tau_ik; 0 otherwise*.

ParamMixRHLP

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