regression

Why pictures are so important when modeling data?

October 31, 2012 | arthur charpentier

(bis repetita) Consider the following regression summary,Call: lm(formula = y1 ~ x1) Coefficients: Estimate Std. Error t value Pr(__|t|) (Intercept) 3.0001 1.1247 2.667 0.02573 * x1 0.5001 0.1179 4.241 0.00217 **... [Read more...]

Conference Presentations

August 15, 2012 | danhocking

I recently gave a talk at the Ecological Society of America (ESA) annual meeting in Portland, OR and a poster presentation at the World Congress of Herpetology meeting in Vancouver, BC, Canada. Both presentations were comparing generalized linear mixed models … Continue reading → [Read more...]

London Olympics 100m men’s sprint results

August 5, 2012 | Markus Gesmann

The 100m mean's sprint finals of the 2012 London Olympics are over and Usain Bolt won the gold medal again with a winning time of 9.63s. Time to compare the result with my forecast of 9.68s, posted on 22 July. My simple log-linear model predicted ... [Read more...]

Plotting 95% Confidence Bands in R

July 26, 2012 | Daniel Hocking

I am comparing estimates from subject-specific GLMMs and population-average GEE models as part of a publication I am working on. As part of this, I want to visualize predictions of each type of model including 95% confidence bands. First I had to ma...

[Read more...]

London Olympics and a prediction for the 100m final

July 22, 2012 | Markus Gesmann

It is less than a week before the 2012 Olympic games will start in London. No surprise therefore that the papers are all over it, including a lot of data and statistis around the games. The Economist investigated the potential financial impact on spons...

[Read more...]

Short versus long papers, in academic journals

April 24, 2012 | arthur charpentier

This Monday, during my talk on quantile regressions (at the Montreal R-meeting), we've seen how those nice graphs could be interpreted, with the evolution of the slope of the linear regression, as a function of the probability level. One illustrati... [Read more...]

Talk on quantiles at the R Montreal group

April 23, 2012 | arthur charpentier

This afternoon, I will be giving a two-hour talk at McGill on quantiles, quantile regressions, confidence regions, bagplots and outliers. Before defining (properly) quantile regressions, we will mention regression on (local) quantiles, as on the gr... [Read more...]

Visualization in regression analysis

February 23, 2012 | arthur charpentier

Visualization is a key to success in regression analysis. This is one of the (many) reasons I am also suspicious when I read an article with a quantitative (econometric) analysis without any graph. Consider for instance the following dataset, obtai... [Read more...]

How big is my dog going to get? A regression analysis with R

January 10, 2012 | Stephan

The dog on the left is named Maya. She is a labrador retriever (field line), weighs 18 kilograms and is currently eight months old. My girlfriend and I carry the dog several times a day high in the fourth floor. … Weiterlesen → [Read more...]

Testing for…

October 31, 2011 | CloudStat

Input Output Testing for regression Input: advertising=c(1,2,3,4,5) sales=c(1,1,2,2,4) sales.Reg=lm(sales~advertising) summary(sales.Reg) Output: __ advertising=c(1,2,3,4,5) __ sales=c(1,1,2,2,4) __ __ sales.Reg=lm(sales~advertising) __ summary... [Read more...]

Support Vector Machine with GPU

August 27, 2011 | rtutor.chiyau

Most elementary statistical inference algorithms assume that the data can be modeled by a set of linear parameters with a normally distributed noise component. A new class of algorithms called support vector machine (SVM) remove such constraint. rea... [Read more...]

Model Validation: Interpreting Residual Plots

July 18, 2011 | Daniel Hocking

When conducting any statistical analysis it is important to evaluate how well the model fits the data and that the data meet the assumptions of the model. There are numerous ways to do this and a variety of statistical tests to evaluate deviations from model assumptions. However, there is little ...

[Read more...]

Because it’s Friday: French Press Heat Retention

May 13, 2011 | Adam.Hyland

While responding to this thread on Reddit I made a rough guess as to the heat retention of my french press when completely full of coffee. When I went to bed I realized there was no good reason why I … Continue reading → [Read more...]

Multivariate probit regression using (direct) maximum likelihood estimators

May 11, 2011 | arthur charpentier

Consider a random pair of binary responses, i.e. with taking values 1 or 2. Assume that probability can be function of some covariates . The Gaussian vector latent structure A standard model is based a latent Gaussian structure, i.e. there exi... [Read more...]

R workshop in Hamilton, Ontario, May 24 and 25

April 25, 2011 | Tal Galili

John Fox will be teaching a two-day introductory R workshop at McMaster University in Hamilton, Ontario, on May 24 and 25. The workshop will largely be based on materials [Read more...]

Machine Learning Ex3 – Multivariate Linear Regression

March 29, 2011 | R on Guangchuang Yu

Part 1. Finding alpha. The first question to resolve in Exercise 3 is to pick a good learning rate alpha. This require making an initial selection, running gradient descent and observing the cost function. Read More: 221 Words Totally [Read more...]

A Short Return to the Age-Earnings Profile

March 8, 2011 | Adam.Hyland

Two posts ago I mentioned the age-earnings profile but did not provide a regression of log earnings on wage. I also offered, without evidence, that fitting a simple linear regression would be inappropriate. How do I know that? How could … Continue reading → [Read more...]

More on logging the outcome

March 4, 2011 | nzcoops

This one does my head in. I do it fairly regularly, lots of people do, but I find everytime it comes to interpreting the results I have to slow it right down and go step by step. Answer: When you log the outcome, then on the original scale, for all ... [Read more...]

The cranky guide to trying R packages

February 13, 2011 | John Mount

This is a tutorial on how to try out a new package in R. The summary is: expect errors, search out errors and don’t start with the built in examples or real data. Suppose you want to try out a novel statistical technique? A good fraction of the time ... [Read more...]

New edition of “R Companion to Applied Regression” – by John Fox and Sandy Weisberg

December 10, 2010 | Tal Galili

Just two hours ago, Professor John Fox has announced on the R-help mailing list of a new (second) edition to his book “An R and S Plus Companion to Applied Regression”, now title . “An R Companion to Applied Regression, Second Edition”. John Fox is (very) well known in the R ... [Read more...]

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regression

Why pictures are so important when modeling data?

Conference Presentations

London Olympics 100m men’s sprint results

Plotting 95% Confidence Bands in R

London Olympics and a prediction for the 100m final

Short versus long papers, in academic journals

Talk on quantiles at the R Montreal group

Visualization in regression analysis

How big is my dog going to get? A regression analysis with R

Testing for…

Support Vector Machine with GPU

Model Validation: Interpreting Residual Plots

Because it’s Friday: French Press Heat Retention

Multivariate probit regression using (direct) maximum likelihood estimators

R workshop in Hamilton, Ontario, May 24 and 25

Machine Learning Ex3 – Multivariate Linear Regression

A Short Return to the Age-Earnings Profile

More on logging the outcome

The cranky guide to trying R packages

New edition of “R Companion to Applied Regression” – by John Fox and Sandy Weisberg

regression

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