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

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LIBLINEAR in C\C++ [migrated]

I want to use LIBLINEAR (http://www.csie.ntu.edu.tw/~cjlin/liblinear) directly in my C++ sources. While it seems simple using it in language like MATLAB/JAVA, in C seems very hard; for example, ...
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Formula behind variables importance in linear model with caret library

The caret library can measure the importance of predictors http://topepo.github.io/caret/varimp.html The importance for a Linear Models is computed as: 'the absolute value of the t-statistic for ...
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ARIMA predictions constant

I've created an Arima model based on past forex closing prices using auto arima, which has generated a (0,1,0) ARIMA model. ...
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Do class-conditional densities always have to sum to 1 conditional on the classes? [duplicate]

I read a lesson here: http://www.byclb.com/TR/Tutorials/neural_networks/ch4_1.htm, and noticed that the class-conditional densities did not sum to one (if we drew vertical lines in figure 4.1, the ...
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Best prediction model for binary data

I have a large medical data set (100.000+ patients), and have many variables (but selected 20 most interesting ones - 15 of these are binary). I want to make a model that predict if these patients ...
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Can I Use Distance Matrix (Weighted) For GLM Fit (Using R)

I am new to statistics but a business user liking to base my decisions on prediction models. And I am relatively new to regression. I have data in the below format. (I have used only imaginary ...
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heteroskedasticity problem (White test)

I am not sure if this question belongs here but I am having a try over here. The datafile is ...
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1answer
8 views

Conditional Indicator Coefficients: Multiple Linear Regression in R

I'm trying to create a regression model for a set of data that includes time and temperature, among others, for 30 minutes intervals throughout the course of a month. I want to build a model that ...
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why is linear regression linear in feature space? [duplicate]

I can't remember where I read this, but i don't seem to get this very well. Linear regression is linear in terms of feature space. Could someone give an example of this? The definition of linear ...
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Linear regression model mistakenly gives $R^2$ equal to 1

I'm using R to create a linear regression model from survey data about public sentiment for a new technology. I am encountering a problem where the addition of a new explanatory variable raises the ...
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r linear regression mistakenly giving me r2 value of 1 [duplicate]

I'm using R to create a linear regression model from survey data about public sentiment for a new technology. I am encountering a problem where the addition of a new explanatory variable raises the ...
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error function in linear regression [duplicate]

In linear regression squared error function is calculated as: $$ Error(w) = \sum_{i=0}^{m} W^{T}x_i - y_i $$ In which $W^T$ means the transpose of weights vector. $x_i$ is the ith input in vector x ...
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Regressions. Why a and b explains more than a+b?

So I have sample of 1987 observations. I'm checking how accounting measures can explain stock returns. If I do a regression of stock returns on CFO (cash flow) and Accruals, I get $R^2= 0.075$. But if ...
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2answers
28 views

Null hypothesis for linear regression

I am confused about the null hypothesis for linear regression. If a variable in a linear model has p < 0.05 (when R prints out stars), I would say the variable is a statistically significant part ...
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1answer
21 views

Relationship between 3 variables confused

I am working on analyzing some data for my master's thesis, and I am not exactly sure how to interpret my results. Let's call my variables A, B, and C. Variable A is negatively correlated with ...
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Generate fake data consistent with adjusted R^2 pattern

Is it possible to specify a vector of adjusted $R^2$ values (or any other measure like AIC, BIC, $C_p$) for the set of all possible models in a data set, and then generate data that is consistent with ...
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prediction model [on hold]

i'am a very beginner in Machine learning I've got machine learning course and now I would like to practice it on prediction context. I need your first push and your help I would like to model a ...
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Comparing linear contrast or slopes

I have a very simple question that is bothering me for a while. Imagine if you have a group with N participants, tested on an indice of performance (such as reaction times RT) according to I various ...
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33 views

Asymmetric regression (assymettric loss for regression)

I have a hybrid classification/regression problem. The predicted value can be assumed to be centred around 0. I want to penalize the predictor more, if the predicted value and actual value have ...
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1answer
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Is golden section search considered a fitting (regression analysis)?

I am curious if the Golden section search is a form of fitting (or regression analysis in general)? It does find the extremum, but independent of any functional form (it works without modeling, if I ...
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685 views

Why isn't the holdout method (splitting data into training and testing) used in classical statistics?

In my classroom exposure to data mining, the holdout method was introduced as a way of assessing model performance. However, when I took my first class on linear models, this was not introduced as a ...
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negative b value but positive corelation [duplicate]

In a linear regression, I have 5 independent variables. All put significant impact on dependent variable $(p <.05)$. Four of the variables put positive impact but one independent variable in ...
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2answers
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What is the proper name of a model that takes as input the output of another model?

Thanks in advance for the help. I am writing a paper and for the life of me can't remember the proper term for a model that works as follows. ...
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Test to use for one nominal and one measured variable [on hold]

I have a measurement variable that is dependent and a nominal variable that is independent and has two values: here and not here. What is the best test to use to measure which nominal variable has ...
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interpreting PERMANOVA (adonis function) output?

I am trying to look at expression of some genes and relate the dist matrix (Sm) to a number of different factors that I collected on the individuals (e.g., litter size, licking behavior, group housing ...
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How do panel regression estimates differ from those obtained from multiple time series regressions?

I am trying to familiarise myself with panel regression techniques and I would like to know how the parameter estimates obtained from a panel regression model differ from those obtained from multiple ...
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Is there a default parameter choice for the spike-and-slab prior?

In the spike-and-slab prior, one needs to specify $h_{0j} = P(\beta_j=0)$, which demonstrates our prior belief about how likely $\beta_j$ to be an important predictor. Is there a default choice for ...
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How to explain the correlation between the mean of each element and it's corresponding PC1 coefficient in a data.frame?

I am doing some PCA analysis by R now,I have a data,which is a data.frame:a,ncol(a) =1000,nrow(a)=100,each row represent a sample,each col represent a feature,so when I use R do PCA analysis like ...
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56 views

Plot regression with interaction in R

I did a regression analysis with the following variables: Predictor = dummy variable, dependent Variable = metric, moderator variable = metric. I now want to show my results in a figure. The ...
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38 views

Logistic regression : non exclusive predictors

I am doing a logistic regression . My outcome is a categorical (yes/ no) pain after surgery. The predictors i wish to model for includes the type of anaesthesia , among other predictors. The problem ...
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Linear regression with estimates of error in predictor

I have data with two different kinds of measurements at the same set of $S$ sites. One of these (call it $X$) returns m estimates at each site, which are not necessarily independent of one another. So ...
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Testing correlation and the t-statistic used in Simple Linear Regression

Given $H_0$ : $\rho=0$ and $H_A$ : $\rho\neq0$, we use the test statistic $t_{n-2}$ , which is $\frac{r\sqrt{n-2}}{\sqrt{1-r^2}}$. I have to show that $\frac{r\sqrt{n-2}}{\sqrt{1-r^2}}$ equals ...
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Standard error of regression coefficient without raw data

After searching here: Perform simple regression without raw data I am still curious about this. Is it possible to derive the standard error of a regression coefficient from summary data alone? ...
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How do I report the weights of the most influential features for logistic regression?

I am currently using logistic regression to compute the probability of some event. I randomly split my training/test data and perform cross-validation on the training data, getting a "best model" for ...
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21 views

Significance codes in linear model with factors

I am setting up a linear model in R and need help understanding the significance codes when one of my independent variables is a factor - i.e., dummy variable for each possible value For a scalar ...
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Breusch-Pagan Test in Weighted Least Squares

When fitting an ordinary linear regression model, we can conduct a test for heteroscedasticity by applying the Breusch-Pagan Test. We fit the linear model, calculate the residuals, and then regress ...
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Why is it the case that when we try to fit an OLS model to a system with more variables than observations, that the residuals are zero?

I am trying to fit an OLS model to some data, where the number of variables $k$ is greater than the number of observations, $N$. In this case, it is obvious that we will have a infinite amount of ...
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Co-linear covariate in regression what if take one out?

I understand that there are a few ways to deal with correlated or co-linear covariates ( PLS or AIC, and Lasso) But my problem here is: If you have 2 covariates x1 and x2 that are correlated(you ...
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2answers
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Bayesian Linear Regression

I have the following question concerning Bayesian linear regression on my machine learning assignment: Consider $f = w^Tx$, where $p(w) ∼ N(w | 0, Σ)$. Show that $p(f | x)$ is Gaussian. I ...
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question about using R to find cofindence interval for the subpopulation [on hold]

I am stucking on several statistic questions. I have no idea which direction should i go. Please help! The variables are x=height of father and y = height of corresponding son. The unit is centimetre ...
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Causal links with omitted variables

So I have a fairly basic setup, with $X\rightarrow Y$. However, I've run across a potential third variable, Z, that is probably correlated with both X and Y. However, the causality for Z is unusual ...
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How to build the A MAtrix for a A-Model(Amat) after a REDUCED VAR in R

i have a doubt in how to build the A MAtrix(Amat) for Estimating a SVAR model in R: I estimated a reduced VAR with the GDP, interest rate and inflation variables . With the economic theory and the ...
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Prior for the coefficients of a linear regression model

I have a linear regression model $\bf Y=\bf{X}\bf{\beta}+\epsilon$. I want to assign a prior on $\bf\beta$ in order to derive the posterior predictive model $p(y_{predictive}|\bf{y},\bf{X},\beta)$. ...
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57 views

Bayesian linear regression question

I am doing a problem on Bayesian regression but I'm having a lot of trouble with it. Here is the question: Consider $f=w^Tx$, $p(w)\sim N(w|0,\Sigma)$. Show that $p(f|x)$ is Gaussian. Find the mean ...
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What to do with this non-normally distributed and near-categorical data?

I have a dependent variable (monetary transfers made by 'dictators' in an experimental dictator game) that is non-normally distributed, and which also appears to be multi-modal (it was collected as a ...
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How can the relative importance of a categorical variable in a linear regression model be determined?

A simple example can be seen here:http://www.ats.ucla.edu/stat/spss/output/reg_spss.htm Gender is a dummy coded variable. I completely understand how to interpret this variable. I cannot use the ...
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Linear Regression and error calculation with streaming data [on hold]

How to calculate error when perform linear regression if data is in streaming pattern ?
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Obtaining adjusted proportions with logistic regression

Can I obtain adjusted proportions of a binary variable by using logistic regression? I have a binary variable (normal/abnormal), which I'd like to obtain adjusted prevalence for (i.e the proportion ...