Cross Validated Asked on January 5, 2022

I’m trying to fit a ridge regression model with a single predictor. However, when I try to do so in three different R packages I get the three following errors:

```
Error in colMeans(X[, -Inter]) :
'x' must be an array of at least two dimensions
Error in if (is.null(np) | (np[2] <= 1)) stop("x should be a matrix with 2 or more columns") :
argument is of length zero
Error in colMeans(x[, -Inter]) :
'x' must be an array of at least two dimensions
```

The bottom line from these errors is that x needs to have at least 2 dimensions. Why is this necessary for ridge regression? Does this mean that I can’t use ridge regression with a single predictor? Just seems weird I couldn’t use ridge regression to get regularization for something like a t-test.

Here is my code:

```
library(lmridge)
library(glmnet)
library(ridge)
# data
set.seet(100)
y <- rnorm(100)
x <- rbinom(100, 1, .5)
z <- rbinom(100, 1, .5)
data <- cbind.data.frame(y, x, z)
# ridge
linearRidge(y ~ x, data = data)
# glmnet
glmnet(data$x, data$y, nlambda = 25, alpha = 0, family = 'gaussian', lambda = .5)
# lmridge
lmridge(y ~ x, data = data, scaling = "sc", K = seq(0, 1, 0.001))
```

StatQuest does ridge with one predictor just fine in his video.

https://youtube.com/watch?v=Q81RR3yKn30

The method is somewhat silly to use in a regression with just one parameter, but I am surprised the common software implementation don’t allow it. Perhaps the StatQuest example could make sense in some setting.

But that’s just an issue with the software implementation. You’re still able to write your parameter vector as $hat{beta}_R = (X^TX+lambda I)^{-1}X^Ty$ and do the calculation.

($I$ is the identity matrix; $lambda$ is your ridge regression hyperparameter.)

Another popular software implementation of ridge regression is the sklearn packing in Python. Perhaps give that a whirl.

Answered by Dave on January 5, 2022

0 Asked on February 23, 2021 by afton-nelson

0 Asked on February 23, 2021 by jamzy

1 Asked on February 23, 2021 by fluctuation

1 Asked on February 22, 2021 by bashir

bounds heavy tailed sample size sampling statistical significance

0 Asked on February 22, 2021 by maxbit

1 Asked on February 21, 2021 by tauling

2 Asked on February 21, 2021 by shenflow

1 Asked on February 21, 2021

classification machine learning neural networks regression survival

1 Asked on February 21, 2021 by joel

5 Asked on February 20, 2021 by gnal

2 Asked on February 20, 2021 by roccer

mixed model random effects model regression sample size statistical power

3 Asked on February 20, 2021 by abdu

0 Asked on February 20, 2021 by user307627

1 Asked on February 19, 2021 by daniel-l

boosting classification machine learning multinomial distribution r

0 Asked on February 19, 2021 by amnon

1 Asked on February 19, 2021 by gerg-horvth

7 Asked on February 19, 2021

0 Asked on February 19, 2021 by kyle-pena

false discovery rate fishers exact test hypothesis testing multiple comparisons p value

5 Asked on February 19, 2021 by thomas-fauskanger

1 Asked on February 18, 2021 by statcurious

Get help from others!

Recent Questions

- How Do I Get The Ifruit App Off Of Gta 5 / Grand Theft Auto 5
- Iv’e designed a space elevator using a series of lasers. do you know anybody i could submit the designs too that could manufacture the concept and put it to use
- Need help finding a book. Female OP protagonist, magic
- Why is the WWF pending games (“Your turn”) area replaced w/ a column of “Bonus & Reward”gift boxes?
- Does Google Analytics track 404 page responses as valid page views?

Recent Answers

- Peter Machado on Why fry rice before boiling?
- Joshua Engel on Why fry rice before boiling?
- Lex on Does Google Analytics track 404 page responses as valid page views?
- haakon.io on Why fry rice before boiling?
- Jon Church on Why fry rice before boiling?

© 2023 AnswerBun.com. All rights reserved. Sites we Love: PCI Database, UKBizDB, Menu Kuliner, Sharing RPP