1539 search results for "regression"

sab-R-metrics Sidetrack: Bubble Plots

March 22, 2011
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sab-R-metrics Sidetrack: Bubble Plots

While I had mentioned in my last post that I will cover logistic regression in my next post, I decided that a quick interlude in working with bubble plots would be fun. Bubble plots have become pretty popular recently, especially with all of the Visualization Challenges I've seen around the internet (by the way, I...

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sab-R-metrics Sidetrack: Bubble Plots

March 22, 2011
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sab-R-metrics Sidetrack: Bubble Plots

While I had mentioned in my last post that I will cover logistic regression in my next post, I decided that a quick interlude in working with bubble plots would be fun. Bubble plots have become pretty popular recently, especially with all of the Visualization Challenges I've seen around the internet (by the way, I...

Read more »

Canabalt Revisited: Gamma Distributions, Multinomial Distributions and More JAGS Goodness

March 16, 2011
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Canabalt Revisited: Gamma Distributions, Multinomial Distributions and More JAGS Goodness

Introduction Neil Kodner recently got me interested again in analyzing Canabalt scores statistically by writing a great post in which he compared the average scores across iOS devices. Thankfully, Neil’s made his code and data freely available, so I’ve been revising my original analyses using his new data whenever I can find a free minute.

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sab-R-metrics: Brief Sidetrack for Scatterplot Matrices

March 16, 2011
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sab-R-metrics: Brief Sidetrack for Scatterplot Matrices

In my last two posts I talked about Ordinary Least Squares, then extended this discussion to the multiple predictor case and briefly talked about some of the problems that may arise. These problems can include omitted variable bias, heteroskedasticity, non-normality, and multicollinearity. Most of these problems are relatively minor in practice and have easy fixes,...

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sab-R-metrics: Brief Sidetrack for Scatterplot Matrices

March 16, 2011
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sab-R-metrics: Brief Sidetrack for Scatterplot Matrices

In my last two posts I talked about Ordinary Least Squares, then extended this discussion to the multiple predictor case and briefly talked about some of the problems that may arise. These problems can include omitted variable bias, heteroskedasticity, non-normality, and multicollinearity. Most of these problems are relatively minor in practice and have easy fixes,...

Read more »

Example 8.30: Compare Poisson and negative binomial count models

March 15, 2011
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Example 8.30:  Compare Poisson and negative binomial count models

How similar can a negative binomial distribution get to a Poisson distribution?When confronted with modeling count data, our first instinct is to use Poisson regression. But in practice, count data is often overdispersed. We can fit the overdispersio...

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UAH Temperature Anomalies Following Predictable Pattern

March 14, 2011
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UAH Temperature Anomalies Following Predictable Pattern

In this post I show one simple  and 2 multiple regression models to assess the role of time, El Nino – La Nina SSTA and volcanic activity (SATO) on UAH global temperature anomaly trends. The 3rd model provides a reasonable  … Continue reading →

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Statistical tests for variable selection

March 14, 2011
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I received an email today with the following comment: I’m using ARIMA with Intervention detection and was planning to use your package to identify my initial ARIMA model for later iteration, however I found that sometimes the auto.arima function returns a model where AR/MA coefficients are not significant. So my question is: Is there a

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Hacker News Analysis

March 13, 2011
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Hacker News Analysis

I was playing around with the Hacker News database Ronnie Roller made (thanks!), so I thought I’d post some of my findings. Activity on the Site My first question was: how has activity on the site increased over time? I … Continue reading →

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Using R for Introductory Statistics, The Geometric distribution

March 13, 2011
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Using R for Introductory Statistics, The Geometric distribution

We've already seen two discrete probability distributions, the binomial and the hypergeometric. The binomial distribution describes the number of successes in a series of independent trials with replacement. The hypergeometric distribution describes th...

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