Questions tagged [regression]
Techniques for analyzing the relationship between one (or more) "dependent" variables and "independent" variables.
23,303
questions
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 ...
