Questions tagged [regression]

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

Filter by
Sorted by
Tagged with
3
votes
2answers
358 views

How to accurately quantify forecast uncertainty in a special case of robust linear regression?

If I'm using OLS linear regression, and I want to know the uncertainty of my forecasts I can quantify it using residuals (MSE, median absolute deviation, etc). But if I'm using robust linear ...
9
votes
1answer
445 views

Inference in linear model with conditional heteroskedasticity

Suppose I observe independent variable vectors $\vec{x}$ and $\vec{z}$ and dependent variable $y$. I would like to fit a model of the form: $$y = \vec{x}^{\top}\vec{\beta_1} + \sigma g\left(\vec{z}^{\...
7
votes
2answers
4k views

The “sum” of prediction intervals

Suppose I have a regression model which yields a couple of predicted values with their respective prediction intervals and the random quantity that I am interested in is the sum of (some subset) of ...
2
votes
2answers
602 views

What is an analogue of PCA in the regression context?

I'm writing code to approximate a function $y=f(\vec{x})$ where $y\in\mathbb{R}$ and $\vec{x}\in\mathbb{R}^N$ for medium-sized $N$ ($N$ between 20 and 50, approx.). I have a ton of examples, however, ...
2
votes
0answers
140 views

How do I control for a confounding variable with this distribution?

The short version of my question is: How is it possible to control for a confounding variable that has a Dirichlet distribution? Suppose I have electoral and census data for a large set of cities. In ...
0
votes
1answer
3k views

Iterate through levels of different factors by means of regression

I am a newbie in R programming. I think for most of you my question is a rather simple one. My regression problem is as follows: I have a dataframe containing several numerical attributes and ...
27
votes
2answers
4k views

Meaning of p-values in regression

When I perform a linear regression in some software packages (for example Mathematica), I get p-values associated with the individual parameters in the model. For, instance the results of a linear ...
28
votes
3answers
100k views

How to test the autocorrelation of the residuals?

I have a matrix with two columns that have many prices (750). In the image below I plotted the residuals of the follow linear regression: ...
5
votes
1answer
264 views

How to test the effect of condition on change scores for a possibly ordinal dependent variable?

I have a categorical independent variable (two levels: condition 1; condition 2) and ordinal(?) dependent variables (numerical magnitude shifts (e.g. -3 if there was a decrease in number magnitude ...
5
votes
1answer
1k views

Poisson regression instead of log transformation of a continuous outcome variable? [duplicate]

Possible Duplicate: Poisson regression vs. log-count least-squares regression? This post got me to thinking about when it makes sense to use poisson regression instead of log transforming a ...
2
votes
0answers
271 views

Is it allowed to incorporate static covariates in Mixed effects models with time series data?

I was recently told that it is not allowed to include static covariates in mixed effect models. I can believe that this could be true, however, when I have time series data, and season is a grouping ...
3
votes
1answer
2k views

How do I interpret interaction coefficients in a temporally lagged regression model?

I am running a linear regression on daily price returns and I want to capture the interaction between subsequent returns: $r_{t+1} = \alpha + \beta_1 r_t + \beta_2 r_{t-1} + \beta_3 r_t \cdot r_{t-1} ...
2
votes
1answer
972 views

What does the dashed bounds mean when plotting a contour plot with R GAM?

At the moment I'm trying to interpret the green and red dashed lines in a contour plot when visualizing a generalized additive model (GAM) with R. These two lines seem to be something like confidence ...
0
votes
1answer
798 views

How do I deal with datasets that have many values out of range / over threshold?

I have a dataset of genomic information which I'm going to be comparing with various biochemical markers. Unfortunately a lot of the biochemical markers have limited ranges in their assays, so I have ...
4
votes
2answers
1k views

How can I compare the relative effects between values of a categorical IV?

I am a social science phd student trying to figure out a statistical test for small conference presentation I am working on. However, I realized I don't know how to run the model I want. Some ...
2
votes
1answer
344 views

In SAS, is there a way to iterative refit a regression using different weights for observation with positive residual and negative residuals?

I have fitted a model using proc reg, say, using this proc reg data = mydata; model a = b; run; But in this particular application it is better to over-...
2
votes
2answers
12k views

How to analyse three independent variables and two dependent variables?

I have measured the following variables on 200 individuals. Independent variables: Measures of personality Extraversion Conscientiousness Leader Member Exchange (LMX) quality Dependent variable ...
1
vote
1answer
1k views

Time dummies in ordered probit regression

I am trying to interpret the coefficients on the year dummies in an ordered probit regression. My data is a panel with 20 years. I have included 19 year dummies with the exclusion of the first year. ...
1
vote
2answers
3k views

Regression of Y on different quantiles of X in Stata

I have data on a dependent variable y and an explanatory one, x, and want to find out if there is a non-linear relationship between theses by running regressions where the data is divided in quartiles ...
6
votes
1answer
15k views

How to interpret Zivot & Andrews unit root test?

I'm check the residuals of a linear regression with Zivot & Andrews unit root test. This is the plot: And the results are: ...
1
vote
1answer
1k views

Not usual piecewise linear regression

I know that with fixed breakpoints (for the x variable), piecewise linear regression is easy and linear. However, for a variety of reasons, I would like to fix the breakpoints for the y variables. ...
3
votes
0answers
101 views

What is the distribution of this nearly-Hotelling statistic?

Let $X$ be an $n \times l$ matrix, and $F$ an $n \times p$ matrix, with the rows of $X$ and $F$ drawn i.i.d. from multivariate Gaussians. (The independence applies to rows: the $X$ and $F$ may be ...
1
vote
0answers
175 views

Elliptic regression, basic conceptual question

I'm considering circular regression and elliptic regression on a computational and conceptual basis. If we fit an ellipse to our data then we deal with the principal components as reference for the ...
81
votes
0answers
64k views

How can a regression be significant yet all predictors be non-significant? [duplicate]

My multiple regression analysis model has a statistically significant F value however all beta values are statistically non-significant. All the regression assumptions are met. No multicollinearity ...
4
votes
2answers
323 views

Logarithms and regression

I have a regression where I am trying to predict Y, using several variables. My variables are A, B, C. I'm using R for my analysis. My equation is as follows: <...
4
votes
2answers
3k views

Prediction with GLS

Let's say I build a Generalized Least Squares model. I follow the standard procedure and first estimate a LM model. Then I create an error-response covariance matrix based on the residuals of this ...
2
votes
1answer
9k views

What is a trend line?

Mathematics and Statistics are quite far behind in my educational curriculum, and yet now I seem to need them again, so this set of questions is very basic I suppose: What is a trend line? What ...
4
votes
2answers
2k views

How to draw a random sample from distribution of prediction?

For my microsimulation, I want to use R to predict values and draw a random sample based on this prediction. To clarify my point: I want to simulate the number of chronic conditions people suffer ...
2
votes
2answers
3k views

In SAS, how do I perform a one sided test of the coefficient in a linear regression?

Say I have fitted a model using proc reg data = data; model a = b; run; How do I test if the coefficient of b is, say, less than 1?
4
votes
0answers
135 views

Theoretical corrections of the training error for time series data

With $y_1, \ldots, y_n$ a real valued time series and $\hat{f} : \mathbb{R} \to \mathbb{R}$ a (least square) estimate of the function $y \mapsto E(Y_i \mid Y_{i-1} = y)$ the training error $$\text{err}...
3
votes
1answer
424 views

Sampling from a posterior distribution in SAS

Lets say I have a dataset where I want to estimate the relative risk of outcome X based on a binary treatment level Y, using PROC GENMOD to fit a logistic regression model. I can use the BAYES ...
2
votes
3answers
753 views

A doubt about the cointegration tests

I'm doing Phillips-Ouliaris Cointegration test with po.test function inside tseries library. I have a simple question about the "cointegration". When i do PO test I get the p-value result but I don'...
20
votes
3answers
32k views

When should one use multiple regression with dummy coding vs. ANCOVA?

I recently analyzed an experiment that manipulated 2 categorical variables and one continuous variable using ANCOVA. However, a reviewer suggested that multiple regression with the categorical ...
1
vote
2answers
2k views

Normalisation for regression

First off, I know little about statistics, so some of this question may seem naive. I'm trying to perform linear regression to model the relationship between x and y where: -x is a company's daily ...
5
votes
1answer
2k views

Zero regression coefficient when correlations are not zero

I don't really have a motivation for this - but I was thinking about this and couldn't work it out. Suppose I have a random variables $X$ and $Y$ which are correlated. Is it possible that the ...
2
votes
1answer
413 views

Simple linear regression — through a specific point

In follow up to a question posted here: Constrained linear regression through a specified point What are some ways that we can tell if a simple linear regression model is "good" when we constrain it ...
4
votes
1answer
3k views

R package for smooth transition regression models

Is there a R package that I can use to specify Smooth Transition Models. I'm looking specifically for something that allows me to specify a TAR model for a given time series. In 2008, a package, ...
10
votes
2answers
9k views

When to use Student's or Normal distribution in linear regression?

I am looking at some problems, and in some, to test the coefficients, sometimes I see people using Student's distribution, and sometimes I see Normal distribution. What is the rule?
6
votes
2answers
24k views

Phillips–Perron unit root test instead of ADF test?

I have read that PP unit root is often used in economy. Is it sensible to do both tests (PP & ADF) or is PP test enough?
4
votes
2answers
213 views

What can you do with 'crazy' data?

This question is more about an approach to a complicated data situation rather than particular statistical methods. I'm modeling our organization's electricity bills, and I have monthly billing data ...
10
votes
3answers
40k views

Linear regression with factors in R

I'm trying to understand how exactly factors work in R. Let's say I want to run a regression using some sample data in R: ...
1
vote
0answers
436 views

Why two series are cointegrated but not mean-reverting?

I'm checking a timeserie with: ADF (unitroot) KPSS (unitroot) Phillips-Ouliaris (cointegration) the results are: Phillips-Ouliaris ...
10
votes
1answer
7k views

Can we compare correlations between groups by comparing regression slopes?

In this question they ask how to compare Pearson r for two independent groups (such as males vs females). Reply and comments suggested two ways: Use Fisher's well-known formula using "z-...
9
votes
3answers
4k views

Is there an R implementation to some mixed models quantile regression statistical procedure?

I would like to find some solution for performing a mixed effect model of quantile regression. From my google searching, I was not able to find an R implementation for such a procedure (only warnings ...
1
vote
0answers
1k views

Correct use of partial derivatives? (Example: polynomial regression)

[update] It seems I had my question's original title misfocused a bit; concerning the use of partial derivatives I found some explanation/confirmation in wikipedia's partial derivative There it is ...
1
vote
1answer
4k views

Finding overall p-value for GLS model

Does anyone know how I can find/calculate an overall p-value for a GLS multiple regression model (made with nlme)?
5
votes
1answer
1k views

How to apply Mahalanobis weighted regression in R?

Some research has shown that in linear regression applications the Mahalanobis distance approach can be used to perform regressions that lower the influence of outliers. The idea is that in the ...
2
votes
1answer
86 views

Modelling worst, average and best case capacity of a system

A system has an incoming request rate of N requests per second. The system hosts a pool of x workers where x >= N. Each worker can complete a single request in approximately t seconds. The maximum ...
1
vote
0answers
1k views

Multivariate linear bayesian regression in matlab with normal-gamma assumption for data

for the general case : data is normal-gamma (mean normal and sd is gamma) and I want to estimate the $b$ and $a$ distribution ( they assumed to be normal) in $y=bx+a$ using Bayesian regression. I know ...
7
votes
3answers
3k views

What are the uses and pitfalls of regression through the origin? [duplicate]

Spuriously high R-squared is one of the pitfalls of regression through the origin (i.e. zero-intercept models). If the predictors do not contain zeroes, then is it an extrapolation? What are the uses ...

1
455 456
457
458 459
467