1559 search results for "Regression"

the large half now

October 28, 2012
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the large half now

The little half puzzle proposed a “dumb’ solution in that players play a minimax strategy. There are 34 starting values less than 100 guaranteeing a sure win to dumb players. If instead the players maximise their choice at each step, the R code looks like this: and there are now 66 (=100-34, indeed!) starting values

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R function: generate a panel data.table or data.frame to fill with data

October 25, 2012
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I have started to work with R and STATA together. I like running regressions in STATA, but I do graphs and setting up the dataset in R. R clearly has a strong comparative advantage here compared to STATA. I was writing a function that will give me a (balanced) panel-structure in R. It then simply

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The basics of Value at Risk and Expected Shortfall

October 23, 2012
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The basics of Value at Risk and Expected Shortfall

Value at Risk and Expected Shortfall are common risk measures.  Here is a quick explanation. Ingredients The first two ingredients are each a number: The time horizon — how many days do we look ahead? The probability level — how far in the tail are we looking? Ingredient number 3 is a prediction distribution of … Continue reading...

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Predict User’s Return Visit within a day part-3

October 22, 2012
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Predict User’s Return Visit within a day part-3

Welcome to the last part of the series on predicting user’s revisit to the website. In the  first part of series, I generated the logistic regression model for prediction problem whether a user will come back on  website in next 24 hours. In the second part, I discussed about model improvement and seen the model accuracy.

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Predict User’s Return Visit within a day part-2

October 22, 2012
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Predict User’s Return Visit within a day part-2

Welcome to the second part of the series on predicting user’s revisit to the website. In my earlier blog Logistic Regression with R, I discussed what is logistic regression. In the first part of the series, we applied logistic regression to available data set. The problem statement there was whether a user will return in

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Predict User’s Return Visit within a day part-1

October 22, 2012
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Predict User’s Return Visit within a day part-1

In my earlier blog, I have discussed about what is logistic regression? And how logistic model is generated in R? Now we will apply that learning on a specific problem of prediction. In this post, I will create a basic model to predict whether a user will return on website in next 24 hours. This

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Soccer is all about money (?) – Part 2: Simple analyses

October 18, 2012
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Soccer is all about money (?) – Part 2: Simple analyses

Alright, now we have all the data we need in one dataframe. To make this code work, I assume you ran the code from Part 1. We need the dataframe big.tab.All the data presented here is based on the data from 18/10/2012. You can run an analysis with the actual data or I can do it at...

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Vendor news: TIBCO’s proprietary R runtime; Teradata’s appliance integrates R

October 17, 2012
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Vendor news: TIBCO’s proprietary R runtime; Teradata’s appliance integrates R

In a webinar today previewing Spotfire 5 (scheduled for release this November), TIBCO announced that it will include TERR: The Tibco Enterprise Runtime for R. TERR is a closed-source reimplementation of the R language engine, and not based on the GPL-licensed R project from the R Foundation. Here's the relevant slide from the webinar: By making the TERR engine...

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What a nice looking scatterplot!

October 15, 2012
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What a nice looking scatterplot!

This week, we look at plotting data using scatterplots. I'll definitely have a post on other ways of plotting data, like boxplots or histograms.Our data from last week remains the same:First, a quick way to look at all of your continuous variables at once is just to do a plot command of your data....

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Color Palettes in HCL Space

October 12, 2012
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Color Palettes in HCL Space

This is a quick follow-up to my previous post about Color Palettes in RGB Space. Achim Zeileis had commented that, perhaps, it would be more informative to evaluate the color palettes in HCL (polar LUV) space, as that spectrum more accurately describes how humans perceive color. Perhaps more clear trends would emerge in HCL space,

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