predict.big_SVD {bigstatsr} R Documentation

## Scores of PCA

### Description

Get the scores of PCA associated with an svd decomposition (class big_SVD).

### Usage

## S3 method for class 'big_SVD'
predict(
object,
X = NULL,
ind.row = rows_along(X),
ind.col = cols_along(X),
block.size = block_size(nrow(X)),
...
)


### Arguments

 object A list returned by big_SVD or big_randomSVD. X An object of class FBM. ind.row An optional vector of the row indices that are used. If not specified, all rows are used. Don't use negative indices. ind.col An optional vector of the column indices that are used. If not specified, all columns are used. Don't use negative indices. block.size Maximum number of columns read at once. Default uses block_size. ... Not used.

### Value

A matrix of size n \times K where n is the number of samples corresponding to indices in ind.row and K the number of PCs computed in object. If X is not specified, this just returns the scores of the training set of object.

### Examples

set.seed(1)

X <- big_attachExtdata()
n <- nrow(X)

# Using only half of the data
ind <- sort(sample(n, n/2))

test <- big_SVD(X, fun.scaling = big_scale(), ind.row = ind)
str(test)
plot(test$u) pca <- prcomp(X[ind, ], center = TRUE, scale. = TRUE) # same scaling all.equal(test$center, pca$center) all.equal(test$scale,  pca$scale) # scores and loadings are the same or opposite # except for last eigenvalue which is equal to 0 # due to centering of columns scores <- test$u %*% diag(test$d) class(test) scores2 <- predict(test) # use this function to predict scores all.equal(scores, scores2) dim(scores) dim(pca$x)
tail(pca$sdev) plot(scores2, pca$x[, 1:ncol(scores2)])
plot(test$v[1:100, ], pca$rotation[1:100, 1:ncol(scores2)])

# projecting on new data
X2 <- sweep(sweep(X[-ind, ], 2, test$center, '-'), 2, test$scale, '/')
scores.test <- X2 %*% test\$v
ind2 <- setdiff(rows_along(X), ind)
scores.test2 <- predict(test, X, ind.row = ind2) # use this
all.equal(scores.test, scores.test2)
scores.test3 <- predict(pca, X[-ind, ])
plot(scores.test2, scores.test3[, 1:ncol(scores.test2)])


[Package bigstatsr version 1.5.1 Index]