2126 search results for "regression"

Visualization Series: Using Scatterplots and Models to Understand the Diamond Market (so You Don’t Get Ripped Off)

January 19, 2014
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Visualization Series: Using Scatterplots and Models to Understand the Diamond Market (so You Don’t Get Ripped Off)

My last post railed against the bad visualizations that people often use to plot quantitive data by groups, and pitted pie charts, bar charts and dot plots against each other for two visualization tasks.  Dot plots came out on top. … Continue reading →

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Evolution hospital beds, resources and consumption

January 19, 2014
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Evolution hospital beds, resources and consumption

For this analysis publicly available data from the OECD is used. The time series run from 1975 to 2013 (where available). Let’s focus on Belgium, Germany, France, The Netherlands, United Kingdom, United States, Norway and Switzerland and have a look at their number of hospital beds per 1000 population. The blue line is a trend The post

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Metaphors Matter: Factor Structure vs. Correlation Network Maps

January 17, 2014
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Metaphors Matter: Factor Structure vs. Correlation Network Maps

The psych R package includes a data set called "bfi" with self-report ratings on 25 personality items along a 6-point agreement scale. All the details are provided in the documentation accompanying the package. My focus is how to represent the correlat...

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Fast-track publishing using knitr: table mania (part IV)

January 15, 2014
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Fast-track publishing using knitr: table mania (part IV)

Fast-track publishing using knitr is a short series on how I use knitr to speedup publishing in my research. While illustrations (previous post) are optional, tables are not, and this fourth article is therefore devoted to tables. Tables through knitr is probably one of the most powerful fast-track publishing tools, in this article I will show (1) how...

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I’ll take my NLS with weights, please…

January 13, 2014
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I’ll take my NLS with weights, please…

Today I want to advocate weighted nonlinear regression. Why so? Minimum-variance estimation of the adjustable parameters in linear and non-linear least squares requires that the data be weighted inversely as their variances . Only then is the BLUE (Best Linear Unbiased Estimator) for linear regression and nonlinear regression with small errors (http://en.wikipedia.org/wiki/Weighted_least_squares#Weighted_least_squares), an important fact

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garch models caught in the spotlight

January 13, 2014
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garch models caught in the spotlight

An attempt to clarify the basics. Previously There have been several posts about garch.  In particular: A practical introduction to garch modeling The components garch model in the rugarch package Genesis A reader emailed me because he was confused about the workings of garch in general, and simulation with the empirical distribution in particular. If … Continue reading...

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The Extra Step: Graphs for Communication versus Exploration

January 12, 2014
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The Extra Step: Graphs for Communication versus Exploration

Visualization is a useful tool for data exploration and statistical analysis, and it’s an important method for communicating your discoveries to others. While those two uses of visualization are related, they aren’t identical. One of the reasons that I like ggplot so much is that it excels at layering together multiple views and summaries of Related posts:

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Converting a JAGS model to STAN

January 11, 2014
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For my first experience with STAN I wanted to convert my last JAGS program into STAN. This was a bit more difficult than I expected. The JAGS program was Fe concentration in rainwater including values below detection level.DataData has been explained b...

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Instrumental Variables Simulation

January 9, 2014
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Instrumental Variables Instrumental variables are an incredibly powerful for dealing with unobserved heterogenity within the context of regression but the language used to define them is mind bending. Typically, you hear something along the lines of “an instrumental variable is a variable that is correlated with x but uncorrelated with...

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Instrumental Variables Simulation

January 9, 2014
By

Instrumental Variables Instrumental variables are an incredibly powerful for dealing with unobserved heterogenity within the context of regression but the language used to define them is mind bending. Typically, you hear something along the lines of “an instrumental variable is a variable that is correlated with x but uncorrelated with...

Read more »

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