# Incomplete-class: Class '"Incomplete"' In softImpute: Matrix Completion via Iterative Soft-Thresholded SVD

## Description

a sparse matrix inheriting from class `dgCMatrix` with the NAs represented as zeros

## Objects from the Class

Objects can be created by calls of the form `new("Incomplete", ...)`. or by calling the function `Incomplete`

## Slots

`i`:

Object of class `"integer"` ~~

`p`:

Object of class `"integer"` ~~

`Dim`:

Object of class `"integer"` ~~

`Dimnames`:

Object of class `"list"` ~~

`x`:

Object of class `"numeric"` ~~

`factors`:

Object of class `"list"` ~~

## Extends

Class `"dgCMatrix"`, directly. Class `"CsparseMatrix"`, by class "dgCMatrix", distance 2. Class `"dsparseMatrix"`, by class "dgCMatrix", distance 2. Class `"generalMatrix"`, by class "dgCMatrix", distance 2. Class `"dMatrix"`, by class "dgCMatrix", distance 3. Class `"sparseMatrix"`, by class "dgCMatrix", distance 3. Class `"compMatrix"`, by class "dgCMatrix", distance 3. Class `"Matrix"`, by class "dgCMatrix", distance 4.

## Methods

as.matrix

`signature(x = "Incomplete")`: ...

coerce

`signature(from = "matrix", to = "Incomplete")`: ...

complete

`signature(x = "Incomplete")`: ...

## Author(s)

Trevor Hastie and Rahul Mazumder

`biScale`,`softImpute`,`Incomplete`,`impute`,`complete`
 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13``` ```showClass("Incomplete") set.seed(101) n=200 p=100 J=50 np=n*p missfrac=0.3 x=matrix(rnorm(n*J),n,J)%*%matrix(rnorm(J*p),J,p)+matrix(rnorm(np),n,p)/5 ix=seq(np) imiss=sample(ix,np*missfrac,replace=FALSE) xna=x xna[imiss]=NA xnaC=as(xna,"Incomplete") ```