The parameters of a regression model.

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1answer
29 views

Do Beta weights from regression have error terms?

I am looking at standardized regression weights (i.e., Beta weights). I was thinking of reporting the errors next to the weights in a figure, but upon some thought I was debating whether such errors ...
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0answers
22 views

What is multi run lasso regression?

I have problem in understanding of multi-run lasso regression. Basically, I know what is lasso regression, but don't know what is multi-run lasso regression, which sometimes I see literatures. Does ...
0
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1answer
39 views

comparing R-squared and F-stat

I am doing multiple regression with Gas production (l/d) as response variable, and flow rate (l/h) and COD influent (g/l) as explanatory variables in R. I made two models. ...
0
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0answers
12 views

Standardized coefficients and IV method

In a multivariate regression, suppose we want to calculate the metric coefficients from the standardized ones. Is the method (standardized coeffcient times standard deviation of the dependent ...
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0answers
14 views

Does residual autocorrelation beyond the first lag have any implication in a regular regression?

I have seen the review of a multiple regression analysis using time series with a quarterly frequency. The original modeler advanced that the model's residuals were not autocorrelated by disclosing a ...
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0answers
24 views

What's wrong with my jackknife procedure in R?

Well, the reason I think my jackknife procedure is wrong is that it gives me the same graph as the residuals. Here's the problem description: Use a loop to create n=50 models. In step i, make a model ...
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47 views

How do I get coefficients of a random forest model?

I am using randomForest to generate a model, and at the end I don't know how I can get the final coefficients that the model is fitting. I know that for linear ...
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23 views

Fitting multiplicative model in a Frequentist way in R

Say, I have sensory panel data for 30 products, which are scored by 11 panelist in 2 replicates for different traits. To fit this data,I am using model of the form: yijr = alpha_j + beta_j*theta_i + ...
0
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1answer
25 views

What does “$R^2$ estimates the combined dispersion against the single dispersion of the observed and predicted series” mean?

In a paper I came across the description of $R^2$ as "it estimates the combined dispersion against the single dispersion of the observed and predicted series". I am not able to understand this ...
1
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1answer
18 views

Is a model nested within itself before collapsing categorical variables?

If I have a model with a categorical variable $X_1=\{0,1,2,3\}$ and a continuous variable $X_2$, and I have a regression model that includes an interaction between $X_1$ and $X_2$, then I decide I ...
0
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1answer
31 views

R: Explanation of a multiple linear regression summary [duplicate]

I am quite new with R and while i am able to perform the basics i am not yet able to understand the output results. For example: summary(lmodel) generates the ...
3
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1answer
63 views

Differences-in-Differences coefficients meaning (from Mostly Harmless Econometics)

In Mostly Harmless Econometrics, section 5.2.1 (Regression DD), pages 233-234, equation (5.2.3) defines $Y_{ist}=\alpha + \gamma NJ_{s}+\lambda d_{t}+\delta (NJ_{s}.d_{t})+\epsilon_{ist}$, where ...
0
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2answers
58 views

Intercept parameter, $\beta_0$

I have a hypothetical data given below that consists of 11 pairs of points (xi, yi ), to which the simple linear regression mean function $\mathbb E(y|x) = β_0 + β_1x$ is fit.: ...
2
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2answers
87 views

What do changes in regression coefficients indicate about correlations among predictors?

How do you tell if there is a strong, weak, or no correlation between two predictors if you are only given the regression coefficients from two models. One model contains one predictor and the other ...
2
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2answers
101 views

How to compute the standard errors of a logistic regression's coefficients

I am using Python's scikit-learn to train and test a logistic regression. scikit-learn returns the regression's coefficients of the independent variables, but it does not provide the coefficients' ...
0
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1answer
27 views

data prediction by regression or better ways

I am working on data prediction. Given data of a random variable $X$ and $Y$, find out how to predict $Y$ from $X$. I know how to do it by linear regression, $\hat{Y} = kX + b$. But, here, $X$ is ...
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1answer
27 views

Coefficient marginal to interactions in linear regression

Consider this model: $$y = \beta_0 +\beta_1x_1 + \beta_2x_2 + \beta_3x_1x_2 + \varepsilon$$ Somebody told me today that the coefficient for the main effect of $x_1$ (i.e., $\beta_1$) will be ...
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33 views

coefficients extracted by effects package in R

Consider this logistic regression: mtcars$vs <- as.factor(mtcars$vs) log_reg_mtcars <- glm(am ~ vs*wt +vs*mpg, family = "binomial", mtcars) I tried using ...
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1answer
249 views
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34 views

Alternative to Chow test for equality of estimates, when the data for the 1st group is not available

My goal is to compare published regression weights estimated from a sample in another country, with those of the same model established on our data.There is ample evidence on the web that a Chow test ...
4
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1answer
127 views

Derive Variance of regression coefficient in simple linear regression

In simple linear regression, we have $y = \beta_0 + \beta_1 x + u$, where $u \sim iid\;\mathcal N(0,\sigma^2)$. I derived the estimator: $$ \hat{\beta_1} = \frac{\sum_i (x_i - \bar{x})(y_i - ...
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0answers
49 views

Dealing with multicollinearity by smoothing coefficients?

I would like to perform a linear regression. However, the predictor variables are families of variables indexed by time. Let's say the regression problem is: target ~ ...
0
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1answer
88 views

How can I compare regression coefficients in the same multiple regression model

I think this question has been answered in bits and pieces here and there, but I am still a bit unsure about what the best approach for this is: how to compare two coefficients from a multiple linear ...
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2answers
45 views

Significant first-step coefficient becomes insignificant in second step of hierarchical multiple regression

I've tried to find the answer to this on this website but haven't been able to, so apologies if this has already been resolved. I am carrying out a hierarchical multiple regression. In the first step, ...
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0answers
22 views

R Library for computing cepstral coefficients from Auto-Correlation coefficients

My main goal is to compute cepstral coefficients in R from an ACF vector (Auto-Coorelation function vector with discrete time-step). Correct me if I am wrong in terminology or whatever as I am not a ...
0
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1answer
48 views

Finding an optimal value for parameter given other parameters

I am looking for a way to find an optimal value among several combinations of values. The data looks like this: ...
4
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1answer
53 views

Averaging LASSO coefficients for repeated random partitioning of data

Is it reasonable to average LASSO coefficients from repeated reshuffling of training/test sets? Suppose I randomly divide my data into testing & training sets, then within the training set use ...
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0answers
41 views

Coefficient of determination of a orthogonal regression

Context I must find the general form of a linear equation. The $X$ and $Y$ values are the location coordinates of touches on a screen. I want to find the best fit line, described by equation $mX + nY ...
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1answer
54 views

How to check for linear constraints of coefficients in logistic regression in R?

I have a logistic regression model with several variables. I want to test the hypothesis of, say $a \beta_i = b \beta_j$ for constants $a,b$. I know that this can be theoretically done with an ...
0
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1answer
53 views

Standardised or unstandardised?

I've been trying to teach myself some statistics (all social science-related) using SPSS. It's all going well so far, I'm amazed at how much I'm managing to understand given how terrible I am at ...
3
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1answer
49 views

Problem related to OLS estimators

The problem is: Suppose we fit a model Y = XA βA + ε. However, the true model is Y = XA βA + XB βB + ε. A is kA x 1 and B is kB x 1. Show that the OLS estimates of βA will still be equal if ...
3
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1answer
91 views

Uniqueness of $x'\beta$ even when $\mathbb{E}(x^Tx)$ is not invertible

As discussed in user25658's answer to this question, when one wants to compute $$ \beta = \mathbb{E}(x^Tx)^{-1} \mathbb{E}(x^TY) $$ but $\mathbb{E}(x^Tx)$ is not invertible, $\beta$ is not uniquely ...
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32 views

Comparing effects of slightly different sets of independent variables on multiple dependent variables in logistic regression

I have a problem with logistic regression. I want to find out if there is any effect of social capital variables (civic participation, generalized trust...) on different dependent variables (namely ...
0
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1answer
37 views

Interpreting parameter estimates when multicategorical predictors

I would like some advice on how to interpret parameter estimates with a continuous dependent variable (healthy food consumption) and a 6-category predictor (income, from 1 = lowest income to 6 = ...
1
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1answer
100 views

Why is my coefficient so large?

I have a GLM modeling basketball data where the dependent variable is the proportion of wins for a season. The independent variables are either percentages, or numeric. The family is binomial, and the ...
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0answers
26 views

How to interprete variable coefficients of OLS where variables are expressed in first difference, I(1)?

I have estimated a multivariate regression line using OLS, and all 3 variables were found to be statistically significant. $$d(NER)=.75+.08\times d(CA)+.002\times d(TB)-.003\times d(OFR)$$ Here, ...
1
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1answer
60 views

How to validate “equal slopes” (proportional odds) in ordinal regression

I would like to fit an ordinal regression model using proportional odds. I learned to test for "equal slopes" in order to say something about the model's validity. Therefore, I fit a model with equal ...
2
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0answers
42 views

Calculating standard error of a coefficient that is calculated from other estimated coefficient

I'm working on the Gompertz growth model to fit weight at age: $$ m(a)=m_{\infty}e^{-\gamma exp(-g{1}a)}$$ Where $m_{\infty}$ and $g_{1}$ are coefficients to be estimated. To deal with lack of ...
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62 views

Relation between coefficient of determination, $R^2$, and significance in a regression

I have performed a simple regression of the following form: $y_t$ = $\beta_1x_{1,t}$ + $\beta_2x_{2,t}$ + $\beta_3x_{3,t}$ the $R^2$ turns out to be 38%. $\hat\beta_1$ = 0.7 (significant at the ...
1
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1answer
85 views

Test for differences in coefficients across groups in panel data

I am wondering how to test for differences in regression coefficients across groups in panel data (after a fixed-effects regression). Particularly, I can't think of a solution of how to construct ...
6
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2answers
282 views

Calculate coefficients in a logistic regression with R

In a multiple linear regression it is possible to find out the coeffient with the following formula. $b = (X'X)^{-1}(X')Y$ ...
3
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1answer
129 views

Using the normal equations to calculate coefficients in multiple linear regression

I am trying to understand how to get the coefficient of a multiple linear regression. The formula is: $b = (X'X)^{-1}(X')Y$ I try to calculate $b$ without package and with the ...
0
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2answers
90 views

Compare regression coefficient for different dependent variables

I am currently reviewing a paper in which the authors perform the following analysis. They use the same set of independent variables to explain 3 different variables. The hypotheses are of the form: X ...
3
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1answer
105 views
0
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1answer
111 views

Why is functional form so important when specifying models? [duplicate]

Variables: lprice = log(price of house) ldist = log(distance from incinerator) lintst = log(distance from interstate) 1st regression 2nd regression: In the ...
2
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4answers
81 views

Any test methods to show the linear behaviour of a data set?

I have a data set that has been collected by a set of empirical experiments. Having plotted them on a graph, it seems that the data behavior is linear. On the other hand, some colleagues claim that ...
3
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1answer
76 views

Why signs of coefficients change when doing multivariate vs. univariate logit regression?

Excuse my dumb question, but I did an univariate logistic regression where the sign of the coefficient of my variable was negative (and it was significant). Once I have input it into a multivariate ...
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43 views

How to interpret the coefficients for binormal part in zero-inflated regression?

use zeroinfl {pscl} I specified offset only for the poisson part. The regression estimate zeroes using regressor zeros ...
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0answers
61 views

Using panel OLS coefficients for forecasting - gretl

I conducted a panel OLS regression using gretl, on a balanced panel with around 25 zones and 10 time periods. I would like to use the model to forecast future values of y (dependant variable), given ...