R package forecast v7.2 now on CRAN

September 9, 2016
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R package forecast v7.2 now on CRAN

I’ve pushed a minor update to the forecast package to CRAN. Some highlights are listed here. Plotting time series with ggplot2 You can now facet a time series plot like this: library(forecast) library(ggplot2) lungDeaths <- cbind(mdeaths, fdeaths)...

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R package forecast v7.2 now on CRAN

September 9, 2016
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R package forecast v7.2 now on CRAN

I’ve pushed a minor update to the forecast package to CRAN. Some highlights are listed here. Plotting time series with ggplot2 You can now facet a time series plot like this: lungDeaths <- cbind(mdeaths, fdeaths) autoplot(lungDeaths, facets=TRUE) So autoplot.mts now behaves similarly to plot.mts Multi-step fitted values The fitted function has a new argument h […]

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Several postdoc positions in probabilistic modeling and machine learning in Aalto, Helsinki

September 8, 2016
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This post is by Aki In addition to the postdoc position I advertised recently, now Aalto University and University of Helsinki have 20 more open postdoc and research fellow positions. Many of the positions are in probabilistic models and machine learning. You could work with me (I’m also part of HIIT), but I can also […] The post Several postdoc positions in probabilistic modeling and machine learning in Aalto, Helsinki…

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It’s not about normality, it’s all about reality

September 8, 2016
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It’s not about normality, it’s all about reality

This is just a repost, with a snazzy and appropriate title, of our discussion from a few years ago on the assumptions of linear regression, from section 3.6 of my book with Jennifer. In decreasing order of importance, these assumptions are: 1. Validity. Most importantly, the data you are analyzing should map to the research […] The post It’s not about normality, it’s all about reality appeared first on Statistical…

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Coverage probability of confidence intervals: A simulation approach

September 8, 2016
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Coverage probability of confidence intervals: A simulation approach

The article uses the SAS DATA step and Base SAS procedures to estimate the coverage probability of the confidence interval for the mean of normally distributed data. This discussion is based on Section 5.2 (p. 74–77) of Simulating Data with SAS. What is a confidence interval? Recall that a confidence […] The post Coverage probability of confidence intervals: A simulation approach appeared first on The DO Loop.

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Polling in the 21st century: There ain’t no urn

September 7, 2016
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Polling in the 21st century:  There ain’t no urn

David Rothschild writes: The Washington Post (WaPo) utilized Survey Monkey (SM) to survey 74,886 registered voters in all 50 states on who they would vote for in the upcoming election. I am very excited about the work, because I am a huge proponent of advancing polling methodology, but the methodological explanation and data detail bring […] The post Polling in the 21st century: There ain’t no urn appeared first on…

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research-lies-allegations-windpipe update

September 7, 2016
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Paul Alper writes: Found this today in the Washington Post. Recall that at my suggestion you blogged about this affair previously: http://andrewgelman.com/2016/06/16/research-lies-allegations-windpipe-surgery/ Damn windpipe surgeons, always causing tro...

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The new quantitative journalism

September 7, 2016
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The first of the breed was Bill James. But now we have a bunch: Felix Salmon, Nate Silver, Amanda Cox, Carl Bialik, . . . . I put them in a different category than traditional science journalists such as Malcolm Gladwell, Gina Kolata, Stephen Dubner who are invested in the “scientist as hero” story, or […] The post The new quantitative journalism appeared first on Statistical Modeling, Causal Inference, and…

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Interview With a Data Sucker

September 7, 2016
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A few months ago Jill Sederstrom from ASH Clinical News interviewed me for this article on the data sharing editorial published by the The New England Journal of Medicine (NEJM) and the debate it generated. The article presented a nice summary, but I t...

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“Brief, decontextualized instances of colaughter”

September 6, 2016
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“Brief, decontextualized instances of colaughter”

Bill Jefferys points me to this news article and writes: Looks at first glance like another NPR example of poor statistics, but who knows? I took a look and here were my thoughts, in order of occurrence: NPR . . . PPNAS . . . Also this: “the results were consistent across all the societies […] The post “Brief, decontextualized instances of colaughter” appeared first on Statistical Modeling, Causal Inference,…

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R demos for BDA3

September 6, 2016
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Last year we published some Matlab/Octave and Python demos for BDA3. During the summer my student Markus Paasiniemi ported these demos to R. New R BDA3 demos are now available in github. We hope these are helpful for someone. They are now just R code, although R Markdown would be cool. Btw. we are expecting […] The post R demos for BDA3 appeared first on Statistical Modeling, Causal Inference, and…

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Inane Journal "Impact Factors"

September 6, 2016
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Why are journals so obsessed with "impact factors"? (The five-year impact factor is average citations/article in a five-year window.)  They're often calculated to three decimal places, and publishers trumpet victory when they go from (say) 1.225 t...

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Graph a step function in SAS

September 6, 2016
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Graph a step function in SAS

Last week I wrote about how to compute sample quantiles and weighted quantiles in SAS. As part of that article, I needed to draw some step functions. Recall that a step function is a piecewise constant function that jumps by a certain amount at a finite number of points. Graph […] The post Graph a step function in SAS appeared first on The DO Loop.

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googleVis 0.6.1 on CRAN

September 6, 2016
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googleVis 0.6.1 on CRAN

We released googleVis version 0.6.1 on CRAN last week. The update fixes issues with setting certain options, following the switch from RJSONIO to jsonlite. Screen shot of some of the Google ChartsNew to googleVis? The package provides an interface betw...

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Link: Jérôme Cukier’s Series on Visualization with React

September 6, 2016
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Link: Jérôme Cukier’s Series on Visualization with React

While D3 is the standard way of doing visualization on the web right now, there's a lot of interesting stuff happening in the world of JavaScript framework React. And it turns out, you can do some really interesting visualization stuff with React, once you understand the basics. In a series of very thorough postings, Jérôme Cukier takes you through […]

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The nature of mathematics and statistics and what it means to learn and teach them

September 6, 2016
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The nature of mathematics and statistics and what it means to learn and teach them

I’ve been thinking lately…. Sometimes it pays to stop and think. I have been reading a recent textbook for mathematics teachers, Dianne Siemon et al, Teaching mathematics: foundations to middle years (2011). On page 47 the authors asked me to “Take … Continue reading →

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A Short Guide for Students Interested in a Statistics PhD Program

September 6, 2016
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This summer I had several conversations with undergraduate students seeking career advice. All were interested in data analysis and were considering graduate school. I also frequently receive requests for advice via email. We have posted on this topic...

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astroABC: ABC SMC sampler for cosmological parameter estimation

September 5, 2016
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astroABC: ABC SMC sampler for cosmological parameter estimation

“…the chosen statistic needs to be a so-called sufficient statistic in that any information about the parameter of interest which is contained in the data, is also contained in the summary statistic.” Elise Jenningsa and Maeve Madigan arXived a paper on a new Python code they developed for implementing ABC-SMC, towards astronomy or rather cosmology […]

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Know your data 20: trust and distrust in our surveillance society

September 5, 2016
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A very important article from the Times starts with the following sentence: Want to invisibly spy on 10 iPhone owners without their knowledge? Gather their every keystroke, sound, message and location? That will cost you $650,000, plus a $500,000 setup fee with an Israeli outfit called the NSO Group. In the U.S., there is a disconnect between a populace whose distrust of government is at an all-time high and the…

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Garrison Keillor would be spinning etc.

September 5, 2016
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Garrison Keillor would be spinning etc.

Under the subject line, “Misleading Graphs of the Week,” Bill Jefferys sends along this: I agreed with Bill’s colleague Helen Read who wondered why should the 90th percentile be some magic number? Just change it to 85% or 95% or whatever and all the graphs will look different. Also kinda horrible that they’re presenting percentages […] The post Garrison Keillor would be spinning etc. appeared first on Statistical Modeling, Causal…

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Matlab goes deep [learning]

September 5, 2016
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Matlab goes deep [learning]

A most interesting link I got when reading Le Monde, about MatLab proposing deep learning tools…Filed under: Books, pictures, R, Statistics, University life Tagged: deep learning, Le Monde, Matlab

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conditional sampling

September 4, 2016
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conditional sampling

An interesting question about stratified sampling came up on X validated last week, namely how to optimise a Monte Carlo estimate based on two subsequent simulations, one, X, from a marginal and one or several Y from the corresponding conditional given X, when the costs of producing those two simulations significantly differ. When looking at […]

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In Bayesian regression, it’s easy to account for measurement error

September 4, 2016
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In Bayesian regression, it’s easy to account for measurement error

Mikhail Balyasin writes: I have come across this paper by Jacob Westfall and Tal Yarkoni, “Statistically Controlling for Confounding Constructs Is Harder than You Think.” I think it talks about very similar issues you raise on your blog, but in this case they advise to use SEM [structural equation models] to control for confounding constructs. […] The post In Bayesian regression, it’s easy to account for measurement error appeared first…

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