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Questions tagged [regression]

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

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19 views

Variable Importance for Logistic regression with categorical data?

If I run the logistic regression with X variables containing categorical data. (I do one-hot encoding on categorical data) How do I evaluate the variable importance? Is there any methods or literature ...
1
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1answer
34 views

How to deal with predictions if taking log of dependent variable

I have a very basic question about linear regression. I have a dataset where the response variable is largely skewed to the right -- if I take a log of it, the distribution becomes a lot closer to ...
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0answers
21 views

Regression line equation [on hold]

How i can get the equation of regression line on my plot just like in excel? I can't figure it out... Here's my code: dane<-read.table(file="+.csv", sep=";", dec=",", header=TRUE) dane dane$Q.nC. ...
3
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1answer
35 views

Linear regression where some known records have a measurement error in dependent variable

I am modelling data where the dependent variable is the number of units of a certain product sold each month in each area. In all areas, the product is sold by a chain of shops 'A' and we have exact ...
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1answer
17 views

accuracy and precision in regression vs classification

Are accuracy and precision the same things in regression and classification? In regression: accuracy is bias, and precision is inverse of variance. In classification: accuracy is correct prediction ...
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0answers
9 views

Media engagement/ Visibility [on hold]

I need to calculate share of voice vs share of market in media. I have data that show all mentions related to my company, also social media mentions(followers if there are any) and reach(the ...
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0answers
24 views

How do you design a regression experiment with many variables but samples are expensive?

I want to design an experiment to see which factors affect production quality. Quality can either be a binary response like "good" or "bad" or a quantitative value like noise level. There are 10 ...
4
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1answer
51 views

Interpreting GLM with logged variable

For my logistic regression model I have: glm(reconv ~ -1 + log(precon) + log(age), data = crime, family=binomial) With the following co-efficients outputted from ...
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0answers
47 views

Calculating R-squared using standard errors

I have the following estimated model: $\hat{y} = 0.2857 + 0.8019x_1 - 0.0741x_2$ (the $t$-statistics are $1.8959$, $8.4198$, and $-3.7017$, respectively). Furthermore, I know the sample size $N = 92$,...
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0answers
17 views

Regularized linear regression with class imbalance

I am trying to build a Linear Regression model using a not so big dataset. I'm more comfortable doing classification and I am not really an expert in regression. In classification, I was used to ...
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2answers
28 views

(Multinomial) Logistic regression with missing values

I want to do a (multinomial) logistic regression to predict 5 different physical activity classes based on different variables extracted for each subject. However, I have one variable (i.e., time ...
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2answers
1k views

categorizing a variable turns it from insignificant to significant

I have a numeric variable which turns out not significant in a multivariate logistic regression model. However, when I categorize it into groups, suddenly it becomes significant. This is very counter-...
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1answer
560 views

Why is the intercept typed in as a 1 in stats packages (R, python)

When using statistics software, When defining your linear models, why is the intercept typed in as a 1, rather than "const" or "intercept" or something. What significance does 1 have? Is there some ...
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1answer
15 views

Dealing with negative values in a positive regression

What is the best way to deal with two sets of independent variables that have two different value ranges? I have one data set with values ranging from -1 to 1 and another data set ranging from 0 to 1....
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0answers
18 views

How to prove that conditional distribution for Y given OLS for simple linear regression do not depends on original parameters?

How to prove that for a simple linear regression model: $$y_i=\beta_0+\beta_1 x_i+\varepsilon_i,$$ the conditional distribution $$Y|\hat{\beta}_0,\hat{\beta}_1$$ do not depends on $\beta_0$ and $\...
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0answers
9 views

Need database set on annual income effect on weight with other variables [closed]

looking for a database set with the effect of annual income on weight along with other variables including region, gender, height, etc.
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1answer
40 views

Fitting model without the intercept [on hold]

Suppose I collected data of crop yield at a location for mutliple years and constrcut a model of the form lm(yield ~ drought_index + solar_radiation + heat_stress) ...
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0answers
7 views

Compare means between samples, while controlling for sampling differences - valid to use regression this way?

There are two independent samples of people, drawn from a population of a city at times $t_1$ and $t_2$, a decade apart*. The people were asked rate their preference regarding some question $Q$ on a ...
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0answers
13 views

Interpreting log coefficients in differences model (time series/panel)

I am struggling with the interpretation of coefficients in $\delta(\log y)=\alpha+\beta\delta(\log x)$ Usually in a $y=\alpha+\beta x$ model, $\beta$ represents change in $y$ corresponding to unit ...
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2answers
33 views

What is between regression and ordinal classification (or called ordinal regression)?

There are many articles explaining the difference between regression and ordinal classification, most of them mentioned that regression is for continuous response while ordinal classification is for ...
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2answers
30 views

R - Help interpreting GLM and ANOVA output

Am I correct in understanding that the effects of flood.level and plant.species are significant predictors of Inv.Simpson (my measure of diversity)? Is it also correct to say that the effect of ...
1
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1answer
22 views

Loss function for KNN Regressor

What is the Loss function for KNN Regressor? Would it be similar to OLS? If so what would be the main difference?
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1answer
37 views

Bayesian regression - prior dist for variables

In a multiple Bayesian linear regression model, do all variables (dependent and predictors) get prior distributions? If so, can one mix non-informative and substantive priors in the model? Thanks!
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1answer
14 views

Can we predict the monthly sales amount of the coming month without knowing the values of the independent variables of the coming month

I have a data set where the monthly sales of TMT bars and various other explanatory variables are present from April 2014-March 2018. I need to predict the monthly sales of the coming/next month. ...
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3answers
36 views

Question Regarding Zero Conditional Mean

Hi I am a beginner to econometrics! I have been dealing with bivariate regression. We use the formula $y = \beta_0 + \beta_1 x$. I am told that if $E(u\mid x) \ne 0$ then the estimate of the slope ...
2
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1answer
51 views

How to choose “family” in Generalized Additive Model (GAM)

When modelling a GAM model using mgcv in R, we need to define the family = . I tried some families (e.g., Gaussian, Gamma), R ...
1
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1answer
28 views

Multi-year and multi-location correlation or regression?

I have fire activity data (i.e. number of fires) and a series of factors (e.g. precipitation, tree cover loss, distance to nearest forest, etc...) that can potentially explain it. I have all this data ...
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0answers
27 views

Sampling distributions for the slope coefficient [closed]

I have a question in my exam, which I do not know exactly the answer, Can you please guide me?
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2answers
54 views

What is a 'true' model?

A short question, but I am somehow unable to find any concrete answer. I suppose it means that the model is as good as it can be? Containing all relevant variables and hence not suffering from any ...
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0answers
35 views

Posterior distribution of Bayesian Parameters

I am confused about how to get the posterior distribution of Bayesian Parameters. I have $t = w_1x + w_0 + \epsilon$ with $\epsilon = N(0, \sigma^2)$ How do I find $p(\textbf{w}|x_1, t_1, ...., x_N, ...
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0answers
16 views

How to know whether a random effect or a cluster effect is necessary for a mixed effect logistic regression?

I have 8 variables in my model out of which I have a group which is definitely not a fixed effect. I tried checking the random effect on the basis of the log-likehood test and it seems significant. I ...
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0answers
8 views

RCT statistic help please

I am wondering what statistics to use for the following randomised controlled trial. A between groups design with a control group, group therapy A, and group therapy B. I am measuring pre and post ...
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0answers
10 views

How to calculate One Standard Error rule tuning parameter for prediction error during k-fold CV

I'm trying to wrap my head around exactly how this rule goes into place, so I can use it by hand in other model selection setups. So here's some R code to get it started: ...
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0answers
22 views

Incorporating linear combination predictions into multiple regression

Let's say I have a predictor $p_1$ of the form: $\textbf{y} = f(\textbf{x})$ Let's suppose that I found another predictor $p_2$ of the form: $E[y_1 - y_0] = c$ (e.g. I have a predictor of linear ...
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1answer
55 views

Is it good practice to use Linear Least-Squares with SMA?

I have time-series (daily) data and I want to understand the general trend. My current approach is: Calculate the 7-day simple moving average. Add a line of best fit (linear least squares ...
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0answers
16 views

Impulse response function for MIDAS regression

Consider a MIDAS regression with a single high-frequency regressor $x_{t/m}$ that is observed $m$ times for every observatoin of a low-frequency regressand $y_t$: $$y_t= \sum_{i=1}^p \alpha_i y_{t-i}+...
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0answers
22 views

interpretation of parameter estimates [closed]

pls clear the interpretation of negative coefficient value of independent varibale in respect to dependent variable in the following table. ...
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1answer
15 views

What does linear regressor output mean? I am using tensorflow estimator in R

I try the code at tensorflow in R tutorial (https://tensorflow.rstudio.com/tfestimators/) but I cannot understand the output what the code produces. Code: ...
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1answer
19 views

R: Methodologically sound way to determine which interaction effects to include in logistic regression? glmulti()?

I ran a logistic regression (in R using the glm function) and didn't find significance for a variable I expected to be significant (numerous articles have found significance). When I examined my data ...
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1answer
32 views

Interpret the slope coefficient

The slope coefficient for SO2 is quite small (0.33), especially as compared to the other three slopes). Does this suggest that the effect of SO2 is therefore not very important?
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1answer
24 views

Interpreting regression results with decimal percentage variables

I have a regression where both my Y and X variables are measured in percent (so they are decimals values, mostly less than 0). The coefficient from the regression is 0.43. Is it correct to say that a ...
1
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1answer
27 views

Meaning of residual maker matrix

Suppose that $M_1$ is the residual maker for a unity vector (i.e. a vector made of $n$ 1's). I am told that this matrix, when premultiplying a variable, transforms the variable "into deviations from ...
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0answers
23 views

Can CART models be used to select features for a logistic regression?

Can I use the features selected from the CART(Classification and Regression Trees) model and take those features and then model the logistic regression using those selected features? Then interpret ...
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0answers
8 views

The consequences of ignoring autocorrelation of errors for the LASSO estimator?

In ordinary linear regression, Y = X$\beta$ + $\epsilon$, if the error is autocorrelated, then the assumptions under the Gauss-Markov theorem are violated. For example, autocorrelation violates the ...
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0answers
93 views
+50

Logistic regression including instrumental variable (“ivprobit” in R) has coefficients with much reduced significance

I am trying to run a logistic regression including instrumental variables by using "ivprobit" function in R from the package called "ivprobit". If I do not include the instrumental variable, the "glm"...
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0answers
39 views

PDF of human population weight distribution

I have a lot of data on human weight coupled with information about gender, age, country and platform (desktop or mobile user). Looking something like this: ...
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0answers
26 views

What statistical test should I use for moderation?

I am hoping to test an interaction effect, though being new to statistics/quant research in general, I am a little unsure as to which test would be most appropriate. I have read around using ...
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1answer
12 views

preparing free text column for regression

I have a column X which contains occupation/profession as an independent variable as free text, which is very much correlated with a continuous dependent variable. What techniques do you usually use ...
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1answer
26 views

A regressor failed to learn extreme values

I am working on a regression problem using xgbclassifier (https://xgboost.readthedocs.io/en/latest/python/python_api.html) The output values range from 0 to 10 (log-normal distribution), but when I ...
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1answer
17 views

Proportion/Rate data and zero-inflation (two counts)

I have an experimental dataset which makes use of two counts. Using vague terms, we are studying animals as they become behaviourally inactive and then apply a stimulus once an hour. One of the counts ...