Monthly Archives: February 2014

Bayesian analysis of sensory profiling data

February 2, 2014
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Bayesian analysis of sensory profiling data

I looked at Bayesian analysis of sensory profiling data in May and June 2012. I do remember not being totally happy with the result and computations taking a bit more time than I wanted. But now it is 2014, I can use STAN and I have been thinking about...

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Visualization of AQI

February 2, 2014
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Visualization of  AQI

The day before yesterday is spring festival which is one of the most famous Chinese festivals, and setting off firecrackers outside on New Year Eve is a traditional custom. However, firecrackers will pollute circumstance severely and cause the hazy weather. Of course the pollution of different province is not the same, and through charts we can view the pollution distribution directly. We … Continue reading →

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New Geometry – Ternary Errorbars

February 2, 2014
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New Geometry – Ternary Errorbars

ggtern 1.0.3.1 has introduced a new series of geometries to represent known errors in data, they are relatively easy to use and are along the lines of the geom_errorbar(...) and geom_errorbarh(...) geometries in ggplot2. Analagous the errorbars in ggplot2, in ggtern, the new geometries are thus listed as follows: geom_errorbarT(…) [Tmin,… The post New Geometry –...

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ggtern 1.0.3.1 on CRAN

February 1, 2014
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An update to ggtern, version 1.0.3.1, is now available on CRAN! This version includes a number of updates and functionality, which can be summarized below: Inclusion of USDA Soil Classification Data, accessed by: data(USDA) Creation of New geometries for ternary errorbars, ie, geom_errorbarT, geom_errorbarL and geom_errorbarR Creation of convenience functions (theme_showtitles and theme_hidetitles) for hiding… The post ggtern 1.0.3.1 on...

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Know India through Visualisations – 1

February 1, 2014
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Know India through Visualisations – 1

I'm going to produce just a couple of charts, a teaser of sorts in this post. In the forthcoming posts I'll dig deeper.I was amazed with the existing list of R packages to work with spatial data, without needing to get into much of the technical detail...

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An idiot learns Bayesian analysis: Part 2

February 1, 2014
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An idiot learns Bayesian analysis: Part 2

A week ago, I wrote a bit about my personal journey to come to grips with Bayesian inference. I referred to the epiphany that when we're talking about Bayesian analysis, what we're talking about- in a tangible way- is using and modifying multivariate distributions. This reminds me of the moment, about twenty years ago now,

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Introduction

February 1, 2014
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Through this blog I intend to work on some data analysis projects, publish the results here and get feedback from other data experts. I have exposure to R, Python, MATLAB and would be using suitable one of them based on needs. My interests range from W...

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Pander/Pandoc for Pretty Conversion on the R Studio Server

February 1, 2014
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Eventually we get around to teaching our students to turn in Homework assignments as R Markdown documents, and towards the end of the semester many of them will do a data analysis project, complete with a report generated as an HTML file. But frankly the HTML output is a bit ugly. What if students want something that looks a...

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Bad Bayes: an example of why you need hold-out testing

February 1, 2014
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Bad Bayes: an example of why you need hold-out testing

We demonstrate a dataset that causes many good machine learning algorithms to horribly overfit. The example is designed to imitate a common situation found in predictive analytic natural language processing. In this type of application you are often building a model using many rare text features. The rare text features are often nearly unique k-grams Related posts: Don’t use correlation...

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