# init.ordi {LCAextend}

### Description

computes the initial values of cumulative logistic coefficients alpha for the EM algorithm in the case of ordinal measurements and a product multinomial model.

### Usage

init.ordi(y, K, x = NULL, var.list = NULL)

### Arguments

- y
- a
`n`

times`d`

matrix of ordinal (or discrete) measurements, where`n`

is the number of individuals and`d`

is the number of measurements. All entries must be finite, if not an error is produced, - K
- number of latent classes of the model,
- x
- a matrix of covariates if any, default is
`NULL`

(no covariates), - var.list
- list of integers indicating which covariates (taken from
`x`

) are used for a given measurement (a column of`y`

).

### Details

The function allocates every individual to a class and evaluates the cumulative logistic coefficients for each measurement and each class. Regression coefficients for the covariates are set to 0.

### Values

The function returns a list of one element `alpha`

which is a list of `d`

elements, each element `alpha[[j]]`

is a `K`

times `S-1`

matrix, where `S`

is the number of values of the measurement `y[,j]`

, a row `alpha[[j]][k,]`

gives the the cumulative logistic coefficients of class `k`

and measurement `j`

using `alpha.compute`

.

### See Also

`alpha.compute`

### Examples

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