# All Questions

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### SVD vs PCA for OLS

I know how to calculate PCA and SVD mathematically and I know that both can be applied to Linear Least squares regression. The main advantage of SVD mathematically seem to be that it can be applied ...
1 views

### Why does glmnet in caret give different predictions for different alphas even though lambda is zero?

In R, when using caret to train an elastic net regularization model, I find that different values of alpha give different predictions when the lambda parameter equals zero. This should not be the ...
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### Suitable function to choose the best split in a regression tree/oblivious tree

My main objective is to construct a regression (decision) tree. It is a part of a boosting algorithm using additive regression trees. The first question is what other functions (other than least ...
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### Glmnet Caret Package with small number of observations

I’m attempting to train a data set with 70 predictors, but only 35 observations with glmnet in the caret package. I’m trying to determine the best resampling method. It seems like 35 observations is ...
7k views

### How do I create subscales based on sets of items in SPSS

I have a 37-question scale, where each item belongs to one of four scales. The items for each scale are interspersed. How can I compute a scale score for each of the four scales? I need to be able ...
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### glmnet: How to make sense of multinomial parameterization?

Following problem: I want to predict a categorical response variable with one (or more) categorical variables using glmnet(). However, I cannot make sense of the output glmnet gives me. Ok, first ...
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### overfit gaussian regression

I have recently read a lot of posts about how maximizing the marginal likelihood in Gaussian Regression can cause overfitting. What is the best way out then? If we let the hyperparameters take values ...
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I am conducting a binary regression using different sorts of parametric links (logistic, Pregibon, Aranda-Ordaz, ... see) and I would like to compare their predictive perfomance in a particular data ...
667 views

### Monte Carlo simulation exercise

The assignment is to run a simulation on excel to figure out the probabilities on obtaining a certain goal: John and Jane Doe are planning to save money to pay a house for their 6-month-old son, ...
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### How can MANOVA report a non-significant p-value while LDA results in perfect separation of two groups?

I am new to statistics and currently got a dataset which contains $80$ dependent variables and $1$ independent variable with $2$ groups. MANOVA reports a $p$-value of $> 0.6$ on this dataset. But ...
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### Parameter estimation in log linear models

Can anyone explain to me how parameter estimation is computed in log linear models? I followed this paper which is quite good, however I'm a bit confused in the parameter estimation part which is ...
1k views

### Detecting outliers in count data

I have what I naively thought to be a fairly straight forward problem that involves outlier detection for many different sets of count data. Specifically, I want to determine if one or more values in ...
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### Best practice for dimensionality reduction with PCA and LDA: does it make sense to combine them?

Assume I have a dataset for a supervised statistical classification task, e.g., via a Bayes' classifier. This dataset consists of 20 features and I want to boil it down to 2 features via ...
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### How is MANOVA related to LDA?

In several places did I see a claim that MANOVA is like ANOVA plus linear discriminant analysis (LDA), but it was always made in a hand-waving sort of way. I would like to know what exactly it is ...
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### How does MATLAB compute the correlation coefficient for robust nonlinear least squares?

As part of a much larger project, I was running some fits and compared the results with what a colleague had and I noticed that our correlation coefficients weren't matching. So I have some data, and ...
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### Time Series Anomaly Detection with Python

I need to implement anomaly detection on several time-series datasets. I've never done this before and was hoping for some advice. I'm very comfortable with python, so I would prefer the solution be ...
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### Test whether triplet of numbers is significantly different from $K$ other triplets

Given $K$ triplets $t_k:=(a_k^{(1)},a_k^{(2)},a_k^{(3)}) \in \mathbb{R}^3, k=1,...,K$ and the triplet to test against them $t=(a^{(1)},a^{(2)},a^{(3)}) \in \mathbb{R}^3$. How can one test whether ...