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

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Choosing variable transformations in non-linear relationships

I am confused about how to apply a transformation to my predictor/response variables to test curvilinear relationships. I read about log transformations, polynomials, quadratic functions. But I am not ...
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9 views

Iterative Addition of Variables to Model Based on P Value

Suppose I have 64 columns that I have chosen out of 500+ columns based on the fact that they have the highest pairwise correlation (is this a good way?). I take 16 of these columns and run a simple ...
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1answer
13 views

Sum of Squares Constraint Regularisation

Suppose I have a function $g_0\in L_2(\mathbb{R})$ such that we observe $(X_i,Y_i)$, $i=1,...,n$ such that $$ \begin{align*} Y_i & = g_0(X_i) + V_i \end{align*} $$ We wish to estimate $g_0$, ...
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1answer
17 views

Estimation of regression with autocorrelated errors

In a book it is written that, In regression work we typically assume that the observational errors are pairwise uncorrelated. But in most time series data , the successive residuals have tendency to ...
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15 views

Is it possible to determine the maximum predictive accuracy for a given data set with a linear regression? e.g. max adjusted R^2

For example say there are N independent variables, and you make a fit with three of them that has a decent Adjusted R2, how do you know when to stop? This is a theoretical question.
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1answer
33 views

Good machine learning algo for partial derivatives?

Does anyone know of good robust algos to estimate partial derivatives of a regression model? I am talking about a general regression model like this: $\mathbb{E}(y|x_1, x_2, ... x_n) = f(x_1, x_2, ...
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1answer
30 views

Graphical comparison of regression models

Will a graph on predicted and measured values plotted for two models separately be helpful in comparing them?
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10 views

R Sales Modeling with Non-Replenishing Inventory

I'm working on modeling sales for tickets for a specific event over time. The issue that I'm having is that the inventory does not replenish, so I can't have my model predicting over what I actually ...
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1answer
44 views

Closed form posteriors for a simple bivariate Bayesian regression

I'm analyzing a simple linear regression $Y_{i}$~$a+b*X_{i}+e_{i}$, with $e$ being normally distributed with known variance and where I have normal priors on $a$ and $b$. I'm trying to piece together ...
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1answer
26 views

How can I (Should I?) use logistic regression/the logit function to predict outcome of a tennis match in a simple simulator?

I am trying to create a tennis simulator. Specifically I am trying to make a 'random' simulator so that I can see how many times streaks of wins or losses occur, and then compare this to historical ...
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1answer
35 views

Spatially auto-regressive two-stage model

I'm working on a project in which I use a 'Generalized Spatial Two-Stage Least Squares' model, mostly known as $y= X \beta + \lambda W y + u$ and $u = \rho M u + \epsilon_n$ where $y$ and $u$ are ...
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1answer
25 views

Durbin Watson test statistic

I applied the DW test to my regression model in R and I got a DW test statistic of 1.78 and a p-value of 2.2e-16 = 0. Does this mean there is no autocorrelation between the residuals because the ...
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31 views

Low explained variance in Random Forest (R randomForest)

I am using randomForest in R for regression, I have many categorical predictors (all of them have the same 3 categories (0,1,2)) and I want to see which of them can predict the response (continuous). ...
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14 views

Conditional logistic regression model does not converge but logistic regression model does

I am running an analysis where I have 2500 cases and 2500 controls. The cases have disease A, and the controls do not. I am trying to see if having disease A increases the odds of various diseases. ...
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1answer
11 views

Whether to transform non-normal pre-test when running linear regression on transformed post-test?

I'm running linear regression model on a post-intervention test score controlling for pre-intervention test score. I used Box-Cox transformation on the post-intervention test score to normalize it. ...
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1answer
31 views

Regression on wavy angular data?

I'm a newbie at stats/machine learning so please bare with me. This plot is a result of an experiment that attempts to find the perceived angle of a stimulus. The stimulus is placed at a position ...
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9 views

how to implement linear or non linear regression for 3d position estimation?

I am a beginner in Machine Learning. For my project I need a regression algorithm that can estimate the 3D position of a device based on some constraints (moreover inputs). I know how to implement ...
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2answers
32 views

Modeling trimmed mean

In OLS, the conditional mean $E(Y \mid X)$ is modeled as a function of some regressors $X$, i.e. $$ E(Y \mid X) = X \beta. $$ Is there a regression technique that allows to model the conditional ...
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3answers
28 views

Can you set a minimum limit for the Y-intercept in R?

I have two sets of test scores I'm using to predict future performance, using multiple regression, and I noticed that the y-intercept is negative. This indicates that for a student who scores a zero ...
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1answer
55 views

How to capture & present lm model output from R

After running iterations of lm() in R, I am now stuck with which components of the model's output to present and how to present them. I know that the $R^{2}$ value, ...
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61 views

How to evaluate fit of a logistic regression

I have a set of data points, which exhibit a solid linear correlation $r\approx 0.9$. I am basically plotting population in certain areas against the number of occurrences of a certain phenomenon (so ...
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3answers
121 views

Determination of regression model

I would like to regress total energy expenditure on age, gender, height and weight.But how do I check whether this relationship is linear?
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49 views

For a model like this what performance measures can I calculate and how?

Methods: From the machine learning literature, I understand different parameters can show performance of model in machine learning. I would briefly expand my understanding with confusion matrix: ...
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1answer
16 views

Regression-tree Tuning in a Streaming Setting

Some time ago I went through a NIPS 2013 paper Regression-tree Tuning in a Streaming Setting. The paper proposes a tree-based regressor. Is there any implementation of this algorithm available? (At ...
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1answer
48 views

Cook's Distance

The formula of Cook's distance is $$D_i=\frac{(\hat Y-\hat Y(i))^{\prime}(\hat Y-\hat Y(i))}{p\times MSE}$$ where, $\hat Y$ is the prediction from the full regression model and $\hat Y$ is a ...
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32 views

Groups in linear regression with different intercepts. How do I find the differing variable?

This is more of a conceptual question. I have a coefficient estimate of .80 in a linear regression model with one IV and one dependent variable. However, plotting the data I see distinct groups, ...
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How to apply hurdle models to panel data (using Stata)?

Is it possible to apply hurdle models (like the Craggit, probit and truncated models) to panel data, preferably with fixed effects to control for unobserved heterogeneity? In Stata, the user-written ...
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10 views

How to assess the importance of the features which come from intersection of features of the two models?

I have two models from two different data sets. Model 1 contain 50 features and model 2 contain 40 features. the intersection of features of model 1 and 2 is 10. so how can I assess the relative ...
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1answer
38 views

Model Formulae. correct model?

I'm trying to build the following model in R, however I'm quite confused about the model formulae to use to include an interaction (x1 and x2) $Y_{}=a+b*x_1+cx_2+d(x_1*x_2)$ this intuitive formula ...
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1answer
12 views

Utilizing A Correlation Matrix Derived from a Sparse Matrix

I have large correlation matrix in Excel that I'd like to use to inform my choice of explanatory variables in a multiple linear regression model. One problem is that the initial data was very sparse, ...
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1answer
57 views

Should a Poisson regression be carried out with only 3 data points?

I'm trying to test the relationship between the number of adults counted and the percentage heather cover over 3 areas. The data looks like this: ...
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1answer
15 views

How to compare the nested models which each of them comes from diffrent dataset?

I have four nested models.Every of them learned from different data sets. now I want to compare these models together.normally people try to compute the F-satistics. But for my case, it's bit harder, ...
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27 views

Significance of varibles after stepwise regression

I did stepwise regression with my multiple regression model and using AIC as a measure of fit with the step function in R. Afterwards some variables that the ...
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22 views

T-Tests and Regressions

my supervisor has asked me a few questions that I'm not entirely sure how to answer. For a quick summary, my study includes a small sample of 16. To describe the sample, I compared the scores of the ...
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12 views

predictive validity of personality traits in job performance of employees [on hold]

I am doing Phd research on "Role of personality traits in predicting the job performance of employees". I have a sample of 500 managers and used the big five personality theory to measure traits of ...
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2answers
64 views

Capturing Seasonality in Multiple Regression for daily data

I have a daily sales data for a product which is highly seasonal. I want to capture the seasonality in the regression model. How I can do it? I have read that if you have quarterly or monthly data, in ...
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2answers
29 views

Dealing with Categorical variables in Multiple Regression

I have a data having 2 continuous and 4 categorical variables. Each categorical variable has 3 levels. I want to know how to include the variables in the model. I am using SPSS Variables: Sales - ...
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6 views

Class complexity vs mean absolute error vs mean squared error when doing regression on continuous vars

I am trying to do regression on the weight of fish caught given a number of continuous parameters, using Weka I'm using 1-12 parameters and a sample size of 5000-15000 A typical output is ...
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11 views

Significant variables, but no improvement on predictive ability of model

When running binary logistic regression in SPSS, I obtain first a measure of the predictive ability of a model without independent variables (base model). This is then compared with that of the model ...
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23 views

How to test whether a distribution follows a power law?

I have the data of how many users post how many questions. For example, [UserCount, QuestionCount] [2, 100] [9, 10] [3, 80] ... ... it means each of the 2 users posts 100 ...
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8 views

What is a “concordance score” for regression coefficients?

I came across this "concordance score" in a set of slides called Penalized regression methods for ranking variables by effect size, with applications to genetic mapping studies, by Ji Zhu: $$ ...
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1answer
11 views

Multivariate regression or PCA to reduce response variables?

I hope the title is self-explanatory, but essentially I want to know which method is better: does it make sense to use a PCA to reduce a number of response Y variables and then conduct a univariate ...
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15 views

Calculate coefficients in a ordinal logistic regression with R

Following the question about manually fitting logistic regression, can someone provide the same 'manual' way to fit a ordinal logistic regression with ordered categorical response?
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30 views

Simplifying numerous dummy variables

I'm looking into a regression analysis to compare the time it takes to award public contracts across different countries but holding some other variables constant is proving challenging. The set of ...
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25 views

How to represent bayesian loss function in binary classification

I am studying classification using linear regression . Now, I want to map it in Bayesian regression. Let talk about binary classification using linear regression again. Assume that I have a set ...
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22 views

binary logistic regression in spss version 22

I'm trying to run a Binary Logistic Regression. I have multiple IVs and 1 Binary DV. Can anyone show me how to do this with SPSS v.22? (or which one to select from this list) thank you
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18 views

Number of significant linear predictors if predictors are not independent?

I would like to determine which of a set of candidate predictors $\{x_1, x_2,\ldots, x_n\}$ are significantly relevant to the linear prediction of $y$. Typically, one can compare a full model ...
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32 views

Robust regression in R with robust::lmRob

I am using the lmRob function in R to do my robust regression. In the R documentation of lmRob found here you can set the ...
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21 views

Using the coefficients of regression for giving weight to the data

I want to perform clustering on my data set. I used spectral clustering and obtained an acceptable result. In an effort to (maybe) improve the result, I thought of applying a linear regression on my ...
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1answer
47 views

How to solve for the parameters in a logistic function? [duplicate]

I want to find the parameters of a logistic function. I read the guide here. It has a very clear explanation, but it did not have the final solution that I need. Now, we will consider a basis ...