1571 search results for "regression"

Core not in CiRM

July 27, 2011
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Core not in CiRM

Despite not enjoying this year the optimal environment of CiRM, we are still making good progress on the revision (or the R vision) of Bayesian Core. In the past two days, we went over Chapters 1 (Introduction), 2 (Normal Models), 5 (Capture-Recapture Experiments), and 6 (Mixture Models), with Chapters 3 (Regression), 4 (Generalised Linear Models)

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Smoothing temporally correlated data

July 21, 2011
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Smoothing temporally correlated data

Something I have been doing a lot of work with recently are time series data, to which I have been fitting additive models to describe trends and other features of the data. When modelling temporally dependent data, we often need … Continue reading →

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Smoothing temporally correlated data

July 21, 2011
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Smoothing temporally correlated data

Something I have been doing a lot of work with recently are time series data, to which I have been fitting additive models to describe trends and other features of the data. When modelling temporally dependent data, we often need to adjust our fitted models to account for the lack of independence in the model residuals. When smoothing such...

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Model Validation: Interpreting Residual Plots

July 18, 2011
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Model Validation: Interpreting Residual Plots

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 general acceptance of any of the statistical tests. Generally...

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Correlation Resources: SPSS, R, Causality, Interpretation, and APA Style Reporting

July 17, 2011
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This post provides links to a range of resources related to the use and interpretation of correlations. I wanted to provide a page with links to a number of additional resources that would be useful both for those of my students who might be keen to le...

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Mixture distributions and models: a clarification

Mixture distributions and models: a clarification

In response to my last post, Chris had the following comment:           I am actually trying to better understand the distinction between mixture models and mixture distributions in my own work.  You seem to say mixture models apply to a small set of models – namely regression models.This comment suggests that my caution about the difference between mixed-effect models and mixture distributions...

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Revolution Newsletter: July 2011

July 14, 2011
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The most recent edition of the Revolution Newsletter is out. The news section is below, and you read the full July edition (with highlights from this blog and community events) online. You can subscribe to the Revolution Newsletter to get it monthly via email. Beta Test Revolution R Enterprise 5.0. Are you running R in a Microsoft environment? Revolution...

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About Fig. 4 of Fagundes et al. (2007)

July 12, 2011
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About Fig. 4 of Fagundes et al. (2007)

Yesterday, we had a meeting of our EMILE network on statistics for population genetics (in Montpellier) and we were discussing our respective recent advances in ABC model choice. One of our colleagues mentioned the constant request (from referees) to include the post-ABC processing devised by Fagundes et al. in their 2007 ABC paper. (This paper

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What is your favorite R feature?

What is your favorite R feature?

R (www.r-project.org) is a free and strongly functional language and environment for statistical computing. You can explore data sets, make graphical displays of data, run statistical simulations and many more. If you never used R you should give it a try! R beginners: There are many courses, slides and tutorials available for R beginners. We

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More fun with the Failed States Index (and the State Fragility Index)

July 9, 2011
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More fun with the Failed States Index (and the State Fragility Index)

So the other day’s experiment with the Failed States Index and the Polity Data didn’t yield the linear trend I had originally expected.  After all, the two measure fundamentally distinct things.  But perhaps there’s another dataset which will match linearly.  The same people who made polity also put out a dataset called the State Fragility

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