# Linked Questions

0answers
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### Correlating variables with eigenvalues in principal components analysis [duplicate]

I have the following problem. I'm performing PCA on a series of correlation matrices (Cm), which result from subsequent rolling windows on data time series, which are my basic variables. That means, ...
0answers
179 views

### Does the order of columns matter in PCA for the results? Jumpy factor loadings? [duplicate]

I have six UK inflation time series, starting from Jan 1990 and ending in June 2019. These series as standardized on an expanding window and subsequently forward filled. I use these series to run a ...
0answers
50 views

### Determining the Direction of Eigenvectors in PCA [duplicate]

I'm using R to get the principal components for several datasets. An example result, using prcomp yields: ...
0answers
26 views

### Why are the directions of eigenvectors in SVD and Eigen-Decomposition for PCA opposite? [duplicate]

As you may know, scikit-learn library utilizes singular value decomposition (SVD) of data matrix X to produce eigenvectors for PCA. I decided to code PCA by using ...
3answers
327k views

### Relationship between SVD and PCA. How to use SVD to perform PCA?

Principal component analysis (PCA) is usually explained via an eigen-decomposition of the covariance matrix. However, it can also be performed via singular value decomposition (SVD) of the data matrix ...
3answers
5k views

### Are PCA solutions unique?

When I run PCA on a certain data set, is the solution given to me unique? I.e., I obtain a set of 2d coordinates, based on interpoint distances. Is it possible to find at least one more arrangement ...
2answers
19k views

### Interpreting positive and negative signs of the elements of PCA eigenvectors

If I center my variables and then run a PCA analysis, do I need to interpret negative eigenvectors different than positive eigenvectors? Clarification: In my PCA analysis I have in a component both ...
1answer
2k views

### Reverse the sign of PCA [duplicate]

I'm struggling on getting a good explanation for the unexpected signs of Principal Component for months. I tried to replicate a result and I got exactly the opposite signs for all components. While I ...
2answers
2k views

### Using the 'U' Matrix of SVD as Feature Reduction [duplicate]

This is a follow-up to the question asked regarding SVD and dimensionality reduction (question). In that question I asked how to use SVD for dimensionality reduction. Although not stated, the ...
2answers
1k views

### How does pca() function in Matlab fix the sign of principal components? [duplicate]

PCA gives me loadings with different signs. I understand that I may simply revert them (as explained in this thread), but I need an explanation (my boss insists) of why Matlab implementation gives me ...
2answers
708 views

### How to compare the outputs of two algorithms computing SVD?

For example we have 2 algorithms from R: SVD and irlba and I want to compare them int terms of speed,memory and precision. But I don't understand how to compare output of algorithms, they must be ...
1answer
1k views

### Singular value decomposition procedure in R

I'm trying to follow Prof Strang exercise but I have a problem with the signs of the resultant matrix. He also had a problem with the signs during the exercise, so I have no way to find what is the ...
0answers
358 views

### Is it possible to reverse the sign of factor loadings for one factor? [duplicate]

I just want to confirm if it is possible to reverse the sign (+/-) on the factor loadings of one factor. I run a PAF with Oblimin rotation. I obtained 6 factors but in one of them the items that load ...
0answers
186 views

### Does it mean anything when all items load negatively on one factor? [duplicate]

note: A few people have marked this question as duplicate - But my question here is not answered in the other question. Though a fine distinction, what I was asking about here was not whether the ...
0answers
125 views

### How to reverse the sign of factor loadings in factor analysis? [duplicate]

I'm doing a factor analysis and using the resulting factors in a regression. I'm using SAS. A number of the variables load positively on a factor. In order to make it easier to interpret in the final ...

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