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

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Log-transformed DV and coefficient of interaction term

I am having difficulty interpreting the significance of positive tone (measured as percentage of words in a sentence that are positive in tone) for females and males. The following is the regression ...
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2 views

ML Regression: Rounding up -ve values for predictions to 0 (if -ve outcomes are impossible) before testing algorithm accuracy?

I am working on a Machine Learning linear regression problem where the output cannot be negative. However when I am running my learning algorithm, the predictions for low values in the test data tend ...
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4 views

Interpreting mediated regression

I did a mediated regression according to B&K (1986). I got the following results: IV-DV= B=0.49, p=0.000 IV-MV was significant as well B=0.46 MV-DV was significant B=0.31 IV-MV-DV: IV was ...
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8 views

Maximum likelihood deviance = lowest Bayesian deviance?

I've just run a logistic regression using the standard frequentist maximum likelihood approach and then again using Bayesian MCMC (weak priors, all ~ $n(0, 100)$). I calculated the deviance for each ...
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19 views

Interpretation of X'X and its inverse

I know how to calculate $X'X$ and $(X'X)^{-1}$, and also how to use them in proving ols and a number of other things. What is unclear to me is the interpretation of this matrix. We use it so much and ...
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10 views

What is the difference between skewed logistic regression and rare event logistic regression

I was doing a traffic safety analysis. My understanding is that if I have a sample that the response distribution differs a lot. for example, I have 200 events, but only 20 of them are crashes. I ...
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7 views

Poisson Regression with Temporal Autocorrelation

Wondering if it is possible to specify temporal autocorrelation in the covariance structure (specifically AR1) while using poisson regression in R. In the Zuur 2009 book the authors state "However, ...
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16 views

Questions about ARIMA

I am estimating this model: But I want to do some analysis of the variables before. In particular, I am interested in fitting some ARIMA models. First, I am doing it for the inflation rate in Mexico. ...
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1answer
33 views

Relationship between dependent and independent variables

I tried to develop an empirical equation by using multiple regression analysis. In my case I use aerosol as dependent variables and relative humidity and winds components ($U$ and $V$) as independent ...
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0answers
6 views

Deterministic polynomial trend in Eviews [on hold]

I have a series St, that i need to detrend by regressing on the deterministic polynomial trend (t): St = a(0) + a(1)t + a(2)t^2 + e where a(0), a(1), and a(2) are estimates parameters and e is the ...
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0answers
8 views

problem in shaping unbalance panel data to run mixed multinomial regression?

I have followed 'mlogit' paper to prepare my unbalance panel data for multinomial (panel) regresssion, but I failed to run the panel regression. After reading some posts, I believe I have found a good ...
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10 views

Linear Regression - Which Features Should We Apply a Polynomial Transform to and Why? [on hold]

In which situations would a feature have a polynomial transformation appropriately applied to it, and why would we do this; what ultimate impact does this have on the data. Supposing we select the ...
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9 views

Capturing decreasing influence of IV as distance increases from DV

Case A) Center value (DV) is determined by properties of circle of radius 500 meter (IVs). Using OLS regression for it. We will keep on increasing radius and see at what radius, the r^2 starts to ...
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12 views

sample and subsample regression coefficient comparison

I have a bivariate sample size of 50. OLS regression of these samples results into line: y=β0+β1x+e. I want to know if statistically similar line can be regressed with less number of data points. Is ...
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0answers
9 views

Errorbars for the intersection point of two regression lines [duplicate]

Let's say I have two sets of data and I've fit lines $l_1$ and $l_2$ to each of them. Each line has its own coefficients that have their own confidence intervals. How can I derive the errorbars for ...
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1answer
36 views

What is standardization's effect on p values?

When you standardize variables (prior to linear regression), is it the case that it will always increase the p value of your intercept term close to or to 1? Or, is it the case that your p value on ...
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1answer
44 views

Rejection Region for Likelihood Ratio Test

I have $((Y_1,x_1),(Y_2,x_2),\ldots,(Y_n,x_n))$ where $Y_i$ is distributed as $N(\theta x_i,1)$. I want to find the rejection region $[0, c]$ associated with $\lambda$ for a test with significance ...
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13 views

Interpreting regression results for different units of measure

Could you kindly help me with interpreting the results from the Probit model for different units of measure of the covariates? Consider the Probit Model $$ Y=1\{X\beta+\epsilon \geq 0\} $$ with $\...
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12 views

Centering the design matrix in multiple linear regression

What happens to the ordinary least squares (OLS) (multiple) regression estimates when one centers the explanatory variables in either of the following cases: Including an intercept: assume that the ...
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0answers
8 views

Regressions with fixed predictors and many permutations of the response data - how to present results?

I have a large matrix of species community abundances from many sites (species in columns and site in rows). I also have environmental variable for each site, and am using linear mixed effects models ...
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44 views

Biasing Linear Regression Downward

Given a sample of data whose correlation is known to have a negative impact as x increases, can you bias a positive slope downward, or with the dataset below what would be an appropriate ...
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0answers
14 views

Monte Carlo study - Simple linear regression [on hold]

I generated Monte Carlo code for 100 random observations Y according to this model: Y = β0 + β1x + e, set.seed(123) n=100 b0=2 b1=1 eps=rnorm(100) for(i in 1:n){ x=seq(0,10, length.out = 100) ...
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24 views

Best fit model in R [on hold]

My predictor variable(x) and response variable (y) are as the following. I tried fitting using multi linear regression, polynomial regression etc. I tried removing the influential points found by cook'...
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0answers
30 views

Difference Between Logit Models and Logistic Regression? [duplicate]

I know these two model has different equation, but I am not sure why people use logistic model instead of logit model and vice versa? What is the main reason behind it? If my response variable is a ...
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0answers
20 views

regression change point model

I am novice at best with linear regression models and I am interested to learn how to do a change point model in Python if possible. The data that I analyze is a years worth of electrical energy (kWh) ...
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2answers
36 views

How can we change gender preference into dichotomous variable when the categories are male, female or any in order to conduct logistics regression?

How can we change gender into dichotomous variable when the categories are male, female or any in order to conduct logistics regression? My research is about gender preferences at the time of birth, ...
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2answers
44 views

Logistic Regression: multicollinearity and Kappa statistics

I may be wrong but from my understanding logistic regression requires there to be little or no multicollinearity among the independent variables, and yet Kappa statistics as part of postResample() ...
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13 views

.In Eviews, wald-test and F-test [on hold]

Why is the Wald test presented together with the F-Test in this regression output from E-Views?
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34 views

oaxaca decomposition output

I am trying to decompose the male female wage gap into an explained part and an unexplained part using oaxaca decomposition. I got the following output: gap between log income of male and log ...
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16 views

Models under Regression Analysis list [on hold]

I am compiling a list of models under Regression analysis(Whatever I think is useful for Machine learning) which is divided into two models i.e Parametric and Non-parametric Regression. Got most of ...
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22 views

Residuals Diagnostics Forecasting principales [on hold]

Help me please Are the following statements true or false? Explain your answer. Good forecast methods should have normally distributed residuals. A model with small residuals will give good ...
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0answers
6 views

Justification for converting likert variable to dummy variables set

I am working on my postgraduate research and have a potentially basic question, but I would much appreciated your help. In a multiple regression model with several predictors that are measured on 7-...
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13 views

trainControl Function - knn [on hold]

How can I change the function bellow for just one-fold cross-validation? When I change the argument "number = 5 to number = 1" the function doesn't work. ...
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0answers
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Name for spurious linear Regression Plots

Yesterday I was at a medical conference in which a lot of plots of Point Clouds with linear fits were shown. In many cases the fit seemed (at least to me and colleagues) to be influenced mostly by ...
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0answers
7 views

Robust Regression in MATLAB's robustfit: what is the optimal weight function to tackle heteroskedasticity?

I'm currently performing a linear regression analysis and encountered a fair amount of heteroskedasticity. Increases in predicted values go along with decreases in residual variance. Otherwise, the ...
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33 views

Deriving predictive distribution

In Bayesian Regression, I am confused how to to get $f*$ and $\sigma*$, given $$y^∗ \mid \vec{y}\sim\mathcal{N}(f^∗ , σ^∗ )$$ $$ p(y^* \mid \vec{y}) = \int{p(y^* \mid \vec{w}) p(\vec{w} \mid \vec{y})...
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20 views

Estimating LASSO through Augmented Lagrangian multipliers

Assume a LASSO problem, specified as $$ \operatorname*{argmin}_\beta L(\beta) = \operatorname*{argmin}_\beta \|Y - X\beta\|_2^2 + \lambda\|\beta\| $$ I've found a paper where the authors claim ...
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1answer
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Using categorical feature as both a continuous feature, and also doing One hot encoding. Is this overkill?

I am working on a Machine Learning regression problem, with a data-set where I have data from a period of several years. From the "date" feature, I extracted the week number (0-53). Next I am doing 2 ...
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20 views

Time series data with mixed calendar and fiscal year

I am performing time series analysis with yearly frequently. However I need to regress a data compiled by calendar year against another compiled by fiscal year. Is it possible to deal with this? If ...
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49 views
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SPSS - Binary logistic regression: classification cutoff

Let's say I want to evaluate the predictive value of a continuous variable in the prediction of malignancy (event/status) of a tumour. Malignant = 1 Nonmalignant = 0 In SPSS, I can run a binary ...
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31 views

lasso with NO cross-validation?

Consider this simple example ...
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0answers
43 views

How to prove that the negative log-likelihood for logistic regression is convex?

How to prove that for logistic regression with individual observations, the negative log-likelihood is convex? I found this wonderful post here that explains why the log likelihood of logistic ...
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26 views

How to calculate the variance of y in in the OLS model? [on hold]

When calculating the variance of the coefficients we get something like this: β̂ =(X′X)^−1X′y.(X is the design matrix and β̂ is the coefficient vector) and thus Var(β̂)=(X′X)^−1X′σ^2IX(X′X)^−1=σ^2(...
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13 views

spearman coefficient results [on hold]

Can someone help me interpret these findings?
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35 views

Best Regression model to apply to predict weight

Hi I have to predict weight using BMI and Age. I tried multi linear regression and got following values: Residual standard error: 0.5735 on 92 degrees of freedom Multiple R-squared: 0.7523, ...
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20 views

regression approach for missing data (left censoring?)

I have a regression problem where I want to predict actuals (dependent variable) of some process where I only have values for a small number of independent variables at the beginning of the process ...
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14 views

censored regression problem if dependent variable only above threshold?

I have to predict some continuous dependent variable of samples where the value of this continuous dependent variable is only above a certain threshold (i.e. predict large values). Does this ...
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9 views

Determining the Relationship Between Monte Carlo Breaks and Model Volatility

I'm looking for a statistical test to understand the relationship (if any) between the model volatilities of a stochastic process, and the occurrence of a'break', defined as an instance when an ...
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1answer
36 views

Orthogonality of residuals in linear regression

In multiple linear regression, I came across the statement that both $e$(residual) and predicted $y$ are projections of actual y and $e$ is orthogonal to predicted $y$. I was trying to visualize the ...
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27 views

What does “middle of the data” really mean?

I have some noisy time series data for different climate variables and I want to know overall if they are increasing or decreasing with time. From this Water Resources Statistics Guide, the LOWESS ...