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Results tagged with r
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user 17672
Use this tag for any *on-topic* question that (a) involves `R` either as a critical part of the question or expected answer, & (b) is not *just* about how to use `R`.
2
votes
Aggregating time series data to one variable
These methods are implmented in the MSQC package in R. Analytical procedures for these are implemented in the spc package in R. …
- 2,220
1
vote
Comparing success ratio based on unequal distribution of samples
Propensity score matching can be carried out in R using the MatchIt package. …
- 2,220
2
votes
1
answer
136
views
How to perform augemented DOE in R [closed]
Is there a similar function in R or a way to achieve it with a sequence of calculations (also fine)? …
- 2,220
5
votes
Algorithm and R implementation of sparse PCA
Another good package is the elasticnet package that Zou and Hastie put out. It has the function spca.
Be careful to select a good value of $\lambda$, the sparsity parameter (or vector of them).
I wo …
- 2,220
3
votes
How to compute classification accuracy of PCA?
It may first make sense to think about how PCA can be used to classify
observations in this setting.
PCA is not in itself a classification method. It is a method for fitting a particular type of mod …
- 2,220
2
votes
0
answers
89
views
Using regression fit to compare two groups at a time point
I have estimated a regression model in R with two groups, included as factors. …
- 2,220
2
votes
What is the most sound way to perform variable selection on an lmer() model?
I would recommend the drop1 function in the R package lmerTest. lmerTest::drop1 also produces an F-test: not only is this test more accurate than the likelihood ratio test by lme4::drop1, it also avoids …
- 2,220
1
vote
PCA Transformed data and regression
Here is a description of how to perform PCR in R.
An alternative is to use Partial Least Squares (PLS). … There is a PLS package for R, though it has limited functionality.
Both PLS and PCA can create problems of interpretation since they transform your original data into new variables. …
- 2,220
1
vote
Accepted
Can I remove outliers from a residual plot? Or does this compromise the validity of my model?
A quick search finds, for example, this robust arima package for R. An advantage of using automated outlier detection methods is that the assumptions underlying them are usually well documented. …
- 2,220