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

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Least Squares Regression Step-By-Step Linear Algebra Computation

As a prequel to a question about linear-mixed models in R, and to share as a reference for beginner/intermediate statistics aficionados, I decided to post as an independent "Q&A-style" the steps ...
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18 views

Ordinary and SVM regression fought, who won?

Suppose one would like to construct a regression model for solely prediction purposes. Which one is better and when, ordinary or SVM regression?
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What is the difference between predict() with and without offset-term when using vglm() of the VGAM package in R?

I am fitting a regression model based on the generalized poisson distribution. Here is an example ...
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44 views

How to deal with the “sure probabilty” (p=1) in logistic regression

The model of logistic regression is that: log(p/(1-p) = ...... The most interesting case (for me) is the case that we have p=1 and p=0. But in this case, the ...
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35 views

Time series Analysis using LS

I know this is a bit of a broad question but generally if I have a time series and I want to measure whether it has trend according to time I do the following: I regress the series against time, ...
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15 views

Trying to perform cluster analysis based on multi-variable data?

I’m struggling with how to find clusters/groups in a large set of multivariable data. Problem: Let’s say I have an ecommerce candy store. At my candy store I have various brands of candies(kitkat, ...
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10 views

Monthly indicator variables, decreasing in weight

I have a logistic regression with a response variable that is a proportion and predictors that are dummy variables for the month of the year, along with a few key exogenous variables. My ...
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35 views

Help logistic regression [on hold]

I have to predict a binary variable with logistic regression. The idea is to classify a number of subjects each either sick or not sick. Therefore, I have 11 risk factories for each person and have to ...
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39 views

Lmer v. lm with Dummy Variables. Where Does the Math Differ in a Simple Example?

I am trying to understand the concept of mixed effect along with the R syntax in lme4 with simple scenarios out of the dataset ...
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Interpretation of Saturated Model vs. Model with Interaction and One Main Effect

Say that I have two regressions: 1) $Y_i = \alpha_0 + \alpha_1 X_i + \alpha_2 X_i*Z_i + \epsilon_i$ 2) $Y_i = \beta_0 + \beta_1 X_i + \beta_2 Z_i + \beta_3 X_i*Z_i + \epsilon_i$ $X_i$ and $Z_i$ are ...
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All of the series used in a model must be stationary at the same order of differencing

While practicing VAR analysis, all of the series used in the model must be stationary at the same order of differencing. Is this correct? For example, let $X$~$I(1)$ and $Y$~$I(2)$. Can I use these ...
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36 views

Stein's estimator vs James-Stein estimator

I read a lot of sources concerning stein's estimator and James-Stein estimator. Unfortunately, a lot of sources do not write the correct formulas of each estimator. And so I am now confused!! Kindly, ...
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Determining a fit test for a interupted stochastic data

I have 10s of thousands of linear data tracks (DNA sequence abundances) which I am attempting to classify by their adherence to a theoretical model. My first pass approach was quite naive, defining ...
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15 views

Lowering C parameter increases the number of support vectors

I know that the C (cost) parameter controls the trade-off between model complexity and misclassification. A large C should increase the error weight, and therefore the model complexity. Nevertheless, ...
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29 views

What are the formulae used in R by predict.lm when interval= a) 'none', b) 'prediction', and c) 'confidence'?

The references provided in the R documentation for predict.lm, taken together, actually leave open a number of possibilities for the formulae for confidence and prediction intervals (including the ...
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21 views

How do I calculate clustering of symptoms?

I am trying to assess whether a risk factor (A) has an impact on clustering of 3 types of symptoms (B, C, D). I know that A has a significant association with B, C, and D. So first I did a ...
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10 views

How to evaluate uncertainty estimates in regression?

Some regression algorithms (e.g. Gaussian process regression) can produce uncertainties along with point predictions at test time. These should also be evaluated. How about calculating the Pearson ...
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17 views

How to calculate Accuracy for regression and time series models?

What is the best way to find accuracy for regression? What is the best way to find accuracy for time series models?
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14 views

F-test of joint significance vs multiple t-test for regression parameters? [duplicate]

In the context of linear regression, I don't understand why you need to perform an F-test for the H0 that all parameters are zero, instead of just looking at all the t-tests for each parameter. I ...
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What is the regression test equivalent to a repeated measures (factorial) ANOVA?

As in the title, I'm trying to figure out what would be the regression test equivalent to a repeated measures one- and two-way ANOVAs? So, in the case of having different dichotomous IVs and two ...
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18 views

Backward selection (with fastbw) in penalized logistic regression

I have a dataset with more than 20 predictors and a single binary response variable. With only $n=181$ observations, I decided to apply penalized logistic regression to modeling, with all predictors ...
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43 views

use of dummy variables in regression equation

I have data where the regressor of interest is 7-point Likert scale responses to a questionnaire regarding experiences. These people are answering questions regarding a group with which they have ...
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16 views

Methods to deal with latent variables

I had a general question about methods to adjust for the effect of latent variables (specially variables that are suspected to be confounder) in observational studies. In particular, I'm working on a ...
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8 views

gnet solution path plot in spike slab regression

in spike slab regression in R, please someone answer me that how we comment the plot of gnet solution path below? I know that the blue ones represent the zero and red ones for nonzero but what does it ...
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565 views

Can I use linear regression on this model y = a/b *x + 1/b

Can I use linear regression on this model y = a/b *x + 1/b? y = (1+ax) /b since a/b and 1/b are related I suspect I cannot use linear regression (least square) directly. Is it possible to transform ...
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35 views

Exponential Regression to Forecast Future Growth

I need to use Exponential Regression to forecast the future earnings of a company. I have the past 10 years of quarterly data. I can do linear regression but the data is not in a linear fashion. ...
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Non linear regression using R [on hold]

I am working on a prediction problem for continuous data. I have some data which I want to fit in the equations. It's non-linear in nature. Can anyone suggest me good non-linear regression algorithms ...
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Is glm(A~B*C*D) the same as glm(A~C*B*D)?

When I run these two in R, I get different values. I thought that I should get the same values since it just includes their interaction terms.
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35 views

Various methods for predicting multiple dependent variables (python)

I would like to model and predict multiple dependent variables depending on one or more independent variables. The most straightforward method appears to be multivariate regression. I was wondering ...
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The effect of scale of predictor variables in regression techniques

In polynomial regression, it is recommended to center predictor input variables to break multi colinear relationships of x to x^2. From Wikipedia: The underlying monomials can be highly correlated ...
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29 views

Largest or smallest confidence interval at $\pi_{i}=0.5$ in logistic regression

A binomial GLM can be written as: $Y_{i}\thicksim B(1,\pi_{i})$ $\mathrm{E}(Y_{i})=\pi_{i}$ and $\mathrm{var}(Y_{i})=\pi_{i}\times(1-\pi_{i})$ ...
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10 views

**Kappa measure in Random Forests** [on hold]

Following is the detailed summary of trained model by Random Forests: ...
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23 views

How to forecast (extrapolate) within a (B-)Spline setting

Suppose I observe a random variable $Y$ for a co-variable $p\in\{70,90,100,...,170\}$. My goal is create a forecast of $\mathbb{E}(Y)$ for $p\in\{50,70,...,350\}$, i.e., a wider range of $p$ as ...
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Regression analysis low R2 value - Result interpretation

When I run linear regression on my test data I get the following report: You can find the test data in here. The graph of actual vs predicted looks like: I would like to know if this is fairly a ...
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regression for class variables [on hold]

Suppose i have a dataset "IQ" with variables: iq-Intelligence quotient value, Age, Country, quantitative ability,verbal ability, logical ability. we can say that a person with more score in ...
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logistic regression R and Stata [on hold]

I mostly use Stata for my regression analysis. I want to conduct a logistic regression on a proportion/number of success. Because I receive errors in Stata I did not expect nor understand (if there ...
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JAGS equivalent to R's I() (Inhibit Interpretation of Objects) function?

I'm wondering if anyone has come across the JAGS/BUGS equivalent to R's I() function. I am interested in using this in a polynomial logistic regression, i.e.: mod1 <- glm(Employment ~ Density + ...
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Plotting simulated data points from f(X)+e using R [on hold]

Below is a chart from An Introduction to Statistical Learning by Hastie and Tibshirani. The authors use the chart to explain overfitting. In the chart, Y is the response variable and X is the ...
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27 views

What is cost-sensitive regression?

Is there such a thing as cost-sensitive regression? If so, where can I find information about it? For example, the regression assigns different costs/penalties to different features beforehand.
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Why non-negative regression?

I've seen this as regularization technique: impose that the coefficients are non-negative. When is this a good idea? What's the intuition and logic behind it?
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16 views

Correlation between dependent and independent variables [on hold]

When I did a course on multiple regression in SAS, before proc reg we did proc corr on dependent variable with all the independent variables. I forgot what we are trying to check through it? Is it ...
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Incremental Gaussian Process Regression

I want to implement an incremental gaussian process regression using a sliding window over the data points which arrives one by one through a stream. Let $d$ denote the dimensionality of the input ...
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23 views

Choosing the correct anova model

How does one choose the best model based on ANOVA's result? I mean I have 3 model outputs 1st is linear+all interaction, 2nd is linear+pair wise interaction and 3rd is linear and I am asked to choose ...
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30 views

Customer life time value prediciton [on hold]

I'm interested in predicting lifetime value for new and existing customers. Which data mining techniques are common for this? I've thought of using Linear regression or a multiple logistic ...
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16 views

Can we perform logistic regression on cross section data?

Can we perform logistic regression on cross section data? My friend says that logistic regression only works for panel data.
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38 views

Linear regression results: How to interpret the plot?

I have a dataset where I am comparing two variables, activity is dependent and days_existed is independent. The correlation between the two variables is 0.41 and I ran an OLS linear regression ...
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26 views

regression with scikit-learn with multiple outputs, svr or gbm possible?

I have been trying regression with scikit-learn with a problem with multiple outputs like this: ...
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13 views

Why would standardized betas be high (e.g. .66) but non-significant in moderated regression?

Running a moderated regression using PROCESS macro in SPSS (issue replicated by running the same moderation using mean-centered variables in SPSS linear regression command box), I am finding that the ...
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How to rescale “linear predictor” in drawing nomogram with “rms” package in R? [migrated]

I am trying to draw a nomogram from a logistic regression in R by using the rms package, but currently I have a problem: indeed, I can get the nomogram, but the "linear predictor" axis ranges from ...
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37 views

linear regression: y “percent”, x “year”?

Is "year" as discrete or continuous variable..? is it proper to use linear regression with "year" (every year from 2009 to 2014) on the x axis and "percent" on the y axis..? Simple question from a ...