# dens.prod.ordi {LCAextend}

### Description

computes the probability of an individual's discrete measurement vector for all latent classes under a multinomial distribution product, eventually taking covariates into account. This is an internal function not meant to be called by the user.

### Usage

dens.prod.ordi(y.x, param, var.list = NULL)

### Arguments

- y.x
- a vector
`y`

of values of the ordinal variables (measurements) followed by the values`x`

of covariates, if any, - param
- a list of the parameters alpha (cumulative logistic coefficients), see
`init.ordi`

, - var.list
- a list of integers indicating which covariates (taken from
`x`

) are used for a given type of measurement.

### Details

If there are `K`

latent classes, `d`

measurements and each measurement has `S[j]`

possible values, `alpha`

is a list of `d`

elements, each is a `K`

times `S[j]+length{var.list[[j]]}`

matrix. For a class `C=k`

, `dens[k]=`

, where P(Y_j=y_j|C=k,X_j=x_j) is computed from the cumulative logistic coefficients `alpha[[j]][k,]`

and covariates `x[var.list[[j]]]`

,

### Values

The function returns a vector `dens`

of length `K`

, where `dens[k]`

is the probability of measurement vector `y`

with covariates `x`

, if the individual belongs to class `k`

.

### See Also

See Also `init.ordi`

,

### Examples

Documentation reproduced from package LCAextend, version 1.2. License: GPL