# Tagged Questions

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### How to Reduce Error Term

My question is "What could you do if you wanted to reduce the error term (e)? I know the error term is basically the distance between the line and the point but I don't know how you would reduce it. ...
39 views

### Additional features for regression

I want add to my regression additional features to complicate my model and lower bias, after searching around internet is seems a good idea is to add square features, that can help regression learn in ...
39 views

### Multiple linear regression question

I am running a multiple regression of the form Y = $\beta_0$ + $\beta_1$*$X_1$ + $\beta_2$*$X^2_1$ + $\beta_3$*$X_2$ + $\beta_4$*$X_3$ on a time-series dataset. I want to plot the relationship ...
219 views

### Is there a difference between 'controlling for' and 'ignoring' other variables in multiple regression?

The coefficient of an explanatory variable in a multiple regression tells us the relationship of that explanatory variable with the dependent variable. All this, while 'controlling' for the other ...
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### Coefficients and Standard Errors

We have a last assignment for my poli sci stat class and these two have really got me stumped. We really didn't go over multiple regression very well so if anybody can help, I appreciate it! Your ...
83 views

### Does more variables mean tighter confidence intervals?

Assume that the true (but unknown) relationship in a population between $Y$ and $X1, X2, X3, X4$ is $$Y=\beta_0 + \beta_1 X_1 + \beta_2 X_2 + \beta_3 X_3 + \beta_4 X_4.$$ Further assume that I have a ...
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### Finding optimal cutoff point with two linear regression models

I am trying to get an optimal cut-off value dividing group with minimum sums of squares of residuals (=observed y - estimated y) the model is like below. In group 1 : model y= a1x + b1z + C1v ... ...
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### stepwise selection on Negative Binomial regression model

I know that I can perform a stepwise selection on ordinary linear regression model based on the t-value. but what about Negative Binomial regression model - or GLM in general? Does it theoretically ...
21 views

### Design a Model to Indivisual function when of sum of all Function given

I am working on a data mining projects and I have to design following type of the model. e.g. I have given 4 feature x1, x2, x3 and x4 and four function defined on these feature such that each ...
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### How can I find out how shifts in a country's fiscal policies affect its economic health?

I have the values of certain variables for 20 years for different countries... I am unable to understand how to use the values of a particular variable for 20 years. Could anyone suggest how I should ...
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### How to build the best regression model using stepwise regression?

I have a data set that contains rental cost (Dependent variable) and I have another data sets that are potential predictors like city, area, No. of rooms etc. (Independent variables). I have ...
124 views

### How to prove that $X^T$e = 0

Hi I need to prove that $X^T$e = 0 where e is the residual in multiple linear regression model in matrix algebra? Need some guidance on how to do it... Is there any good pdf for the proofs for ...
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### May I validate a model after shrinkage?

I am doing a logistic regression using Frank Harrell's rms package. I went through the steps shown in his book and the rms ...
105 views

### What model should one use for this short time series?

Below I have quarterly total sales on the left (dependent variable), and a sample of the sales on the right. The two variables share a correlation of 98.7%. What model should I use to predict X? ...
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### Regression estimate of a non-negative variable

I have to estimate linear weight $\beta$ for regression $Y \sim \mathbf{X}$, where $Y$ are non-negative samples. If I perform vanilla regression (lets assume ridge regression) it will find $\beta$ ...
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### Nonconstancy of error variance

If the residuals show that the non constancy of the error variance is clearly present, does it mean that your regression results are completely invalid?
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### Confidence interval for multiple regression parameter

I'm given the least squares model: Y = B0 + B1x1 + B2x2 + B3x1x2 Y = 12 -2x1 + 7x2 +5x1x2 n = 20 as well as some RSS's ...
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### Setting intercept to zero: Will this change both standard deviations and the error term?

After running a single regression with a forced zero intercept, I understand that $\beta$ (slope(s)) will change as $\alpha$ (intercept) will be set to zero. Easy. $\rho = \beta(\sigma_x / \sigma_y)$ ...
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### Best regression model, given coefficient of variation $R^2$ and mean-squared error

If you have 3 separate models in a multiple regression problem (and 3 ANOVA tables), which would be best given that you have the coefficient of determination, $R^2$, and mean-squared error values? So ...
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### Partial F ratio from ANOVA table

In multiple regression, if you have just an ANOVA table, and nothing else, no specific data, how can you do a partial F test on X1, given X2 is already in the model? So, you have the ANOVA table: ...
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### Linear regression with independent variables with varying proportions

I am looking to do a linear regression on two independent variables that will be present in varying proportions. For example trying to do a linear regression on $Y$ which is payment behavior (payback ...
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### Parameters as sort of weights

I'm after model that would spit out weights where the weights sum to 1 rather than parameters themselves. This is what I have done: I have fitted 3 logit models ...
60 views

### Difference between model / line?

I have a dataset. I'm asked to write out the linear regression model. I'm also asked to calculate the least squares regression line. What's the difference?? [[EDIT]]
81 views

### A summary of different cases of interaction effects, how do you interpret?

I know there are lots of questions/answers about dealing with interaction effects in regressions on this site, but I think there is a need to summarize a bit. I don't know if there is a standard way ...
115 views

### Data cleaning for large sample data set in multiple linear regression

I have 70,000 observations for my depentant variable. I have 12 independant variables. After removing zero value and error and missing value form my data set, my data reduced to 4000. Can I still do ...
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### Model Estimation

How can I estimate a model where Y ~ X1 + X2 + X3 X1 ~ Z1 + Z2 X2 ~ Z1 + Z2 X3 ~ Z1 + Z2 where Y may/may not be correlated with Z1 and Z2. Is there a R procedure that I could use to estimate the ...
215 views

### Correct way to compare two (very) different regression models?

I'm working with some piecewise linear regression models, and I'd like to compare their predictions with those produced by multiple (weighted) linear regression models. Both models describe the same ...
86 views

### Is there a regression method for fitting general N-order polynomials of two or more variables?

I would like to fit a general N-order polynomial of two or more variables. For example, consider (for reference) the general second-order polynomial in two variables $x$ and $y$: ...
186 views

### How to interpret parameter estimates correlated with the intercept parameter estimate?

I have performed a regression in SAS and extracted the estimated correlation matrix of the parameters, which includes the intercept. One of my variable parameters has a strong correlation to the ...
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### Regression with rank order as dependent variable

I have data on 44 firms that have all been ranked by an expert. The "best" firm has rank 1, the second best has rank 2, ..., the last one has rank 44. I have a bunch of explanatory variables and ...
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### Linear regression 3 variables formula for slope coefficient estimates

Okay so I think I found a formula for the coefficient estimates but it is not very concise. It has like 6 sum of squares but it is in a single fraction so it is calculable. I was wondering what the ...
46 views

### Forecasting customer value as a function of digital engagement?

I want measure the value of a digital engagement, or a digitally engaged customer. Therefore I want to build a model to predict customer value as a function of digital engagement with a given digital ...
148 views

### Quantile regression

I have a question regarding quantile regression. Supposing that I have 10000 observations with one response variable and several predictor variables in a dataset collected each year over several ...
449 views

### Using logistic regression for a continuous dependent variable

I got a revision for my research paper recently and the following is the reviewer's comment on my paper: results obtained from one model is not quite convincing especially linear regression ...
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### “Block-corrected values” in R

I'm helping with a plant fertilization study where 3 treatments (additional nitrogen, phosphorus, and potassium) were applied, sometimes in combination, across multiple blocks. We suspect that there ...
68 views

### Definition of multivariate regression coefficient

I know that the regression coefficient of $Y$ and $X$ is defined as $$\beta(Y,X) = \frac{\mathrm{Cov}(X,Y)}{\mathrm{Var}(X)}$$ Does this expression also hold in a multivariate regression with $Y$, ...
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### Confusion related to multitarget regression

I have a bunch of features/xs and a bunch of targets ys. I want to run a linear regression on this. I don't know if I should take every y to be independent and learn separate regression models or just ...
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### Selection of regressors

I have a question about the package leaps which I am using for model selection. I would like to compare 4 different selection methods: forward, backward, stepwise and best subset. I used the code ...
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### Python packages for numerical data imputation [closed]

I am working with multivariate numerical data with a lot of missing values (so dropping all entries or columns with missing data is not an option). Is there a Python package for data imputation? I ...
137 views

### Is my parameter estimate significant or not?

DISCLAIMER: This question was sent to Stata list today, but so far nobody has answered. NOTE: I use Stata here, but actually I don't think the question is software-specific. Hi, I would appreciate ...
53 views

### Variable not significant in log specification

I am estimating a model which gives me significant parameter estimates for my variables of interest. However, when I use the log version of the model log(dependent)=log(independent), I don't get ...
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### How to select the degree of polynomial multiple regression?

I have around 50 dependent quantities (regressor variables). I want to find the best relation between the response variable data and regressor variable data. I tried multiple linear regression with ...
128 views

### Multiple linear regression where explanatory variables almost always equal 0

I'm trying to do a multiple linear regression model to correlate a dependent $Y$ variable (normally distributed) against a set of 642 variables. These 642 variables codify for the presence or absence ...
75 views

### Should a non-significant adjustment variable be kept in a regression model? [duplicate]

I'm working with a structural equation model to study influenza infection risk. As age is a known risk factor to explain infection, I therefore adjusted my infection outcome on the subjects age class. ...
36 views

### Right or wrong controls

Is it correct to control for variables that might have the inherited structure of the dependent variable? Two cases below: 1) Variables that are not considered as predictors, but rather a ...
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### System missing data

I'm currently struggling with my data. My dependent variable has an N of 332, out of which 180 are system missing, because of the routing in the questionnaire: First question: Have you taken in ...
127 views

### Predicting count data (clicks) based on the words used in a title

So I have a data set of articles like so. ‘Difference of Python and Ruby’ 537 ‘Advanced Tutorial on Python’ 1438 ‘HTTP library’ 134 ...
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### Unexpected intercept in linear regression with dummy variables

I am modeling a binary DV with a factor variable consisting of 8 clasess. I know I could just analyse the distribution of the DV across all factor classes but I will add more variables and wanted to ...