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

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How should I model a [0,1] censored variable?

I have a variable which is based on a count of occurances devided by the total number of potential occurences for each unit. This variable thus varies between zero and one. It should be used as a ...
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10 views

Choosing a Model for Inference

I'm trying to understand what factors contribute to the a certain outcome which is a ordered factor variable. In order to just understand which factor is statistically more significant than the ...
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13 views

Regression from matrix to vector

I'm used to regressions between a set of input and output vectors . Now I need to model the relation between a set of matrices and a set of vectors. So each realisation is a matrix and each output is ...
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1answer
17 views

Which regression model to choose? [duplicate]

I have two models, one lm(y ~ x1 + x2 + 0) which gives me a close to 0.90 something $R^2$ and another model lm(y ~ x1 + x2) ...
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1answer
16 views

Regression analysis and new data

I've got X and Y variables for performing a linear regression on them. How can I calculate the probability that a new entry belongs to the model I have fitted on X and Y?
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1answer
23 views

Posterior of a simple Bayes linear regression

In the context of simple linear Bayesian regression, why or when is it appropriate to define the posterior as $p(\beta, \sigma^2|y)$ and not $p(\beta, \mu|y)$?
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14 views

approaches for computing confidence band and prediction band for general regression analysis and predictive models

In linear regression model, the predict in R is able to calculate the confidence band and ...
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1answer
28 views

Regarding 10 fold cross validation

I am bit confused regarding the application of 10 fold cross validation steps. To be specific, I have made a multiple regression model (except model validation) and the model does not predict ...
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7 views

How to choose right step size for alpha in the Elastic net using glment package?

I'm using glmnet to learn different Elastic net regression.as you know, Elastic net would perform at least as good as Lasso regression. but it's not the case for me and Lasso perform better than ...
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20 views

Regression with related coefficients

I've worked out that some physical process has the form $y = ax_1 + (1-a)x_2$, and would like to perform regression to find $a$. I thought about multiple regression of $y$ on $x_1$ and $x_2$ and ...
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1answer
21 views

Finding regression coefficient only with matrix correlation

How do I find Regression coefficient if data provided is only matrix correlation table? Here is example for x1 matrix correlation. ( I also have x2,x3,x4, but only provided x1 in here) for the sake ...
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1answer
22 views

Need help with multivariate multiple regression models

I want to predict more than one dependent variable by running one model, I thought that we can use Multivariate Multiple Regression Model. But I don't know how to do it with Excel or R. Can anyone ...
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18 views

optim() for multi variable returns values on the boundary in R

I would like to use function optim() in R to minimise the target function. The two optimised parameters both have constrains. I have created a test sampel data. ...
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Simple Linear Regression - Prediction Interval and Non-constant variance

I have two questions about a simple linear regression model. I want to use test1 scores to predict test2 scores. I am using R software. x=test1, y=test2, Let's say that both tests are scored from 1 ...
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1answer
28 views

How to implement reduced-rank regression in R?

How can I fit reduced-rank regression with continuous response in R? I found the package VGAM but it only fits for discrete distributions...
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2answers
31 views

'Punishment Function' in Number of Knots in Splines?

I was considering using natural cubic splines for my prediction problem when I had a thought: In Ridge Regression, you set out to minimize the equation; \begin{equation} F(X)=\lambda\sum_i ( b^2)+ ...
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14 views

Regression - Censored Data

I am trying to create a linear regression model which will predict test scores of students based on previous test scores. x=test1, scores range from 1:100 y=test2, scores range from 2:50 I have ...
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12 views

AR(n) model with exponents

When we discuss a (time-series) model $AR(n) = \Sigma_{i=0}^n Y_{t-i} + \cdots + \epsilon_t$, we use $n$ to refer to the number of time steps back the autoregression includes. In other such models, we ...
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19 views

difference between confidence interval and prediction interval in the context of regression analysis and predictive modeling

When building prediction models, I always see the following concept 1) Confidence interval for regression model 2) Prediction interval 3) Confidence interval for predicted value I can understand ...
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1answer
38 views

Post-hoc after GLM: What does it exactly say?

Background: I have been asked to model the change of weight of a few animals undergoing experimentation via a simple GLM (General Linear Model). The data looks something like this. Note that all data ...
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21 views

What is the “pdm” stat in the “rms” R package?

I am new to the world of Regression in statistics and I have been doing a research in which I am building an ordinal logistic regression model (ORM). In order to fit my ORM model, I am using the 'orm' ...
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22 views

Model Selection with Competing risks in Cox regression

When doing cox proportional hazards regression one often has competing risks. The typical approach for this is to fit separate cox proportional hazards models for each risk, censoring the competing ...
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1answer
30 views

R adds unexpected variable to interaction model

Not sure if this is more of a programming question (in which case please move to stack overflow) or a statistical model question (in which case, please read on!) I'm exploring a data set and doing ...
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4 views

Finding an area of low variance for (robust) linear regression

In order to determine a function for a Good-Turing approximation of the number $N_r$ of distinct words that occur $r$ times in a hypothetical language corpus, I'd like to run a (log-)linear regression ...
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13 views

Comparing influence of single independent variable on two dependent variables (time series)

Scenario description: Temperature has been measured at $k+2$ different depths in a borehole. Measurements of the temperature were taken once each hour over a period of about 3 months. So observed data ...
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13 views

Trend analysis on time intervales

I am trying to do trend analysis on tweets. I am still confused. The classical model is based on computing the frequency of items, to say that the item with big number of frequency is the trending ...
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51 views
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44 views

Nature of the Relationship between Predictors and Dependent in Regression

Given the interpretation of regression coefficients for continuous predictors is of the form: a one unit increase in the predictor leads to a "coefficient" unit increase in the: dependent (linear ...
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27 views

How can I create a linear regression model with some negative coefficients in R? [duplicate]

What I'm trying to do is to construct a linear model in a form like $$ Y = \beta_0X_0-\beta_1X_1+\beta_2X_2 + \beta_3 $$ where $\beta_0$, $\beta_1$ and $\beta_2$ are coefficient of predictors $X_0$, ...
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1answer
26 views

What is Nadaraya-Watson Kernel Regression Estimator for Multivariate Response?

Given a regression setting with covariates $X_{n \times m}$ and response $Y_{n \times p}$ where $p>1$, i.e the responses are vector-valued or multivariate, is there a Nadaraya-Watson estimator for ...
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2answers
60 views

Negative fitted values in OLS regression

I am running a regression where my dependent variable is a cross-section of variances. Therefore, I require my predicted values (fitted values) to be positive. However, when running a simple OLS ...
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1answer
33 views

How to perform regression with a sensitivity analysis in R

Without using non-base packages like plm, how can I perform a fixed effects regression in R with a sensitivity analysis for one or several other variables? Some ...
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1answer
19 views

How to find optimal penaltyparameter C for SVM (regression)

I am training an svm regressor using python sklearn.svm.SVR From the example given on the sklearn website, the above line of code defines my svm. ...
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3answers
59 views

Regression function of “non-regressible” data

I have some background in probability, and now trying to understand statistics, which sometimes leads to the questions of the following kind. Let $X$ and $Y$ be two random variables that represent the ...
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1answer
30 views

Bootstrap glm and extract pvalue

I am running a glm model using bootstrap, I can extract the coefficient mean and the confidence intervals for all the factors in my model. But how can I get the pvalue from there? Model: ...
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77 views

How to compute confidence bound in linear regression

In a simple linear regression problem, let $A$ be an $m\times n$ matrix of samples, $A=[x^T_1; x^T_2; ...;x^T_m]$, $w$ is the $n\times 1$ parameter vector, and $b$ is $m\times 1$ response vector. The ...
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1answer
11 views

main effects of moderating variables

I am sorry if this is very trivial and a repetition. I could not find a direct question on the website that addresses my question I am studying the relationship between X1 (independent variable) and ...
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16 views

Can I interpret a simple slope if the product is not significant?

I used Hayes' PROCESS macro to run a simple regression. The interaction product was not significant (p=0.13) however the conditional effect (simple slope) was significant (at high levels of the ...
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1answer
18 views

Estimate effect on mean of dependent variable of an increase in the independent variable in a linear regression

Suppose I have the linear regression equation: Y = B0 + B1(x) How do I find the estimated effect on mean Y of an additional 50 to x? I believe this is the multiplicative effect.
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43 views

About stepwise regression and correlation

I am trying to fit a model to some observed data with the least squares method. Now, I am at the stage where I have run a stepwise regression (traditional), with Entry level $=0.025$ and Stay level ...
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9 views

Regression Output from R [on hold]

I'm trying to regress the outcome variable "count number" on its lag and season, where 1,2,3,4 represent spring, summer, autumn and winter, respectively. However, I got some very weird output from R. ...
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14 views

Excluding Outliers and Influential Observations ($R^2$ and AIC/BIC)

I am working on a cross-sectional data set relating mortgage payments to debt-income ratios. I have some extreme outliers and experimented with excluding them from the model (some 30 observations of a ...
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17 views

One Step Ahead Forecasts Using Predict() in R

I just fit a model to a time series. I am now required to generate a 10-year extrapolation forecast of my model. My model includes a time term, a time^2 term, 12 seasonal dummies, and 4 lagged ...
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1answer
47 views

Comparison of predictive models

I am trying to compare the predictive ability of various models in predicting survival in patients. I would like to examine the predictive performance of each model using 4 tests: squared Pearson ...
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39 views
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41 views

Econometric Model : [on hold]

I don't understand which model to use for "Socioeconomic factors affecting non farm labour supply for households" . I am working with Household Income and Expenditure Survey data (HIES) Bangladesh, ...
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27 views

Handling Sparse Data Frames - algorithm selection

I am new to machine learning/statistical modelling. I am trying to run a classification on a highly sparse dataset with 100 features, most of which are categorical (TRUE/FALSE) with the remaining ...
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0answers
13 views

Relation of distributions

I want to predict a distribution using multiple related distributions. One method is to use multiple regression (the model specification is that the dependent variable, yi is a combination of the ...
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0answers
8 views

Binary Logiistc regression and covariates in SPSS

When running binary logistic regression, where there is an dependent variable, multiple independent variable and covariates, where do I put the covariates in SPSS? Would they go in the covariate box ...
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13 views

R: Error with mlogit Conjoint modelling - system singularity

I am building choice models on a dates about coffee preferences. I have 5 alternatives: Brand, Cup, Price, Certification and Local Community Support. The data looks like this: ...