1682 search results for "Regression"

Predictors, responses and residuals: What really needs to be normally distributed?

February 18, 2013
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Predictors, responses and residuals: What really needs to be normally distributed?

Introduction Many scientists are concerned about normality or non-normality of variables in statistical analyses. The following and similar sentiments are often expressed, published or taught: "If you want to do statistics, then everything needs to be normally distributed." "We normalized…Read more →

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Automatic spatial interpolation with R: the automap package

February 17, 2013
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Automatic spatial interpolation with R: the automap package

In case of continuously collected data, e.g. observations from a monitoring network, spatial interpolation of this data cannot be done manually. Instead, the interpolation should be done automatically. To achieve this goal, I developed the automap package. automap builds on… See more ›

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Version 1.0 of multilevelPSA Available on CRAN

February 14, 2013
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Version 1.0 of multilevelPSA Available on CRAN

Version 1.0 of multilevelPSA has been released to CRAN. The multilevelPSA package provides functions to estimate and visualize propensity score models with multilevel, or clustered, data. The graphics are an extension of PSAgraphics package by Helmreich and Pruzek. The example below will investigate the differences between private and public school internationally using the Programme of International Student Assessment...

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Large claims, and ratemaking

February 13, 2013
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Large claims, and ratemaking

During the course, we have seen that it is natural to assume that not only the individual claims frequency can be explained by some covariates, but individual costs too. Of course, appropriate families should be considered to model the distribution of the cost , given some covariates .Here is the dataset we’ll use, > sinistre=read.table("http://freakonometrics.free.fr/sinistreACT2040.txt", + header=TRUE,sep=";") > sinistres=sinistre...

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Exposure with binomial responses

February 9, 2013
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Exposure with binomial responses

Last week, we’ve seen how to take into account the exposure to compute nonparametric estimators of several quantities (empirical means, and empirical variances) incorporating exposure. Let us see what can be done if we want to model a binomial response. The model here is the following: , the number of claims  on the period  is unobserved the number of...

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Happy Birthday Florence Henderson

February 9, 2013
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Happy Birthday Florence Henderson

As a celebration of Florence Henderson’s 79th birthday (on February 14), I have created this scatterplot to use in my regression course. The plot depicts the relationship between time spent on mathematics homework outside of school (expressed as z-scores) and … Continue reading →

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Quantifying the international search for meaning

February 9, 2013
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Quantifying the international search for meaning

Inspired by Preis et al.’s article Quantifying the advantage of looking forward, recently published in Scientific Reports (one of Nature publishing group’s journals), I wondered if similar big-data web-based research methods might address a question even bigger than how much different countries wonder about next year. How about the meaning of life. Who is searching

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Extracting the Epidemic Model: Going Beyond Florence Nightingale Part II

February 7, 2013
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Extracting the Epidemic Model: Going Beyond Florence Nightingale Part II

This is the second of a two part reexamination of Florence Nightingale's data visualization based on her innovative cam diagrams (my term) shown in Figure 1. Figure 1. Nightingale's original cam diagrams (click to enlarge)RecapIn Part I, I showed that FN applied sectoral areas, rather than a pie chart or...

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Modelling memory and news trajectories

February 6, 2013
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Modelling memory and news trajectories

Modelling memory In the text below I present two models I've made to quantify and visualise the diverging trajectories of memory and news events, and conclude that linear regression may be used to test which model best describes the story. First, though, I contextualise this with an illustration from the...

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The new Stan 1.1.1, featuring Gaussian processes!

February 6, 2013
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The new Stan 1.1.1, featuring Gaussian processes!

We just released Stan 1.1.1 and RStan 1.1.1 As usual, you can find download and install instructions at: http://mc-stan.org/ This is a patch release and is fully backward compatible with Stan and RStan 1.1.0. The main thing you should notice is that the multivariate models should be much faster and all the bugs reported for The post The...

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