# Questions tagged [regression]

Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.

18,205 questions
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### Generate scenarios of multiple related parameters

Assume I have three industry datasets: interest rates, inflation and unemployment. Data contains information of last ten years and it's monthly. Now, I would like to create N possible scenarios of ...
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### What do we mean by saying “Explained Variance”

I'm studying linear regression and there is a concept I can't wrap my head around. I've heard many times the expression "the independent variable explains $a$% of the variance of the dependent ...
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### “Forward search” methods for outlier detection etc. in regression

I am reading Robust Diagnostic Regression Analysis by Anthony Atkinson and Marco Riani. They propose a robust "forward search" method for detecting outliers and other problematic data in regression (...
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### Which regression should be used when both dependent and independent variables are nominal? All have multiple classes

The aim is to find which team will win the game based on head to head data. All the variables are nominal and have more than 2 classes. For now, I have coded them as dummy variables and have performed ...
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### How to perform a linear mixed model with time series?

My data measures the width of plant(in cm) over the period of 5 days while taking into consideration the liquid used to treat the plants and my plants are clustered, my data look like this: ...
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### Decision on instant T depends on decision on T-1

I'm trying to model decision making in a linear fashion: Lm(decision~ var1 + var2) However, i believe that decision in instant T dependant on the previous decision on T-1 with the same independants ...
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### Using SVR to model simple data set

I have a fairly simple data set that I gathered from running workloads on a Hadoop Cluster. My goal is to model the running times of this application based on the feature variables of interest. The ...
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### why data normalization is important for models when parameters can manage the feature weight/importance

When we study about normalization, various facts are given to explain the necessity. The most important of all is that: Normalized column if in higher range than others can have more impact on ...
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### How regression trees split, when all the Features and target have only continuous values

Can anyone please explain how splitting is performed in regression trees when we only have continuous features. I have referred to different papers, but all I could find is formulas or theorems. Can ...
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### Partial Least Square - choosing number of factors

I'm trying to implement PLS in R (using the package "PLS") to a time series consisting on realized variance of the S&P 500 and macroeconomic variables, however, I've notice they use cross-...
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### Updating regression solutions for removing a regressor without the original dependent variable

Note: This question is analagous to the question I asked here except instead of adding a column, I am removing it. I am interested in a linear regression on the model; $Y= X\beta + \epsilon$ And I ...
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### GLM: Modelling proportional data - account for variation in total sample size

When I am sampling the proportion of a sub-group of animals to the total number of animals within a sample, I can feel quite confident (after taking into account environmental factors) that I have a ...
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### Updating regression solutions for a new regressor without the original dependent variable

Note: This question is analagous to the question I asked here except instead of a removing column, I am adding it. I am interested in a linear regression on the model; $Y= X\beta + \epsilon$ And I ...
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### which normalization method is appropriate for regression problem?

I have a regression problem. I have 3 features: X1 is in the range (0.7 , 1.3) X2 is in the range (0.4 , 0.5) X3 is in the range (4.5 , 5.5) and Y is in the range (115 , 719) I started trying ...
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### Gaussian Processes: advice on proper optimization settings for simple model?

I am trying my hand at Gaussian Processes with GPflow (basically using this basic example as my guide), and am experiencing difficulties fitting some basic periodic data which I generated. My code: <...
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### Confidence interval for extrapolated value?

I have data that is modeled according to the equation: $$\tag{1} \frac{\Delta p}{L} = \frac{\mu}{k}\frac{q}{A}+\beta \rho \frac{q^2}{A^2}$$ The variables $\Delta p, L, \mu, q, A$ and $\rho$ are all ...