368 search results for "evaluation"

Spatial Randomness Evaluation in R: Monte Carlo Test

May 14, 2012
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Spatial Randomness Evaluation in R: Monte Carlo Test

This post is a some kind of reply to this one.So our goal is to determine whether our point process is random or not. We will use R and spatstat package in particular. Spatstat provides a very handy function for this, that uses K-function combined with...

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Are students’ teaching evaluations influenced by instructors’ looks?

August 3, 2011
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Are students’ teaching evaluations influenced by instructors’ looks?

Are students' teaching evaluations influenced by instructors' looks? ggplot2 may help find the answer.The recent release of RcmdrPlugin.KMggplot2 has made ggplot2 available to those who prefer GUI to the command line interface. With the new plugin for ...

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Forecast estimation, evaluation and transformation

November 9, 2010
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Forecast estimation, evaluation and transformation

I’ve had a few emails lately about forecast evaluation and estimation criteria. Here is one I received today, along with some comments. I have a rather simple question regarding the use of MSE as opposed to MAD and MAPE. If the parameters of a time series model are estimated by minimizing MSE, why do we

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RSI(2) Evaluation

June 28, 2009
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RSI(2) Evaluation

Despite my best efforts, it's been a month since the last post of this series. The first post replicated this simple RSI(2) strategy from the MarketSci Blog using R. The second post showed how to replicate the strategy that scales in/out of RSI(2). ...

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Using closures as objects in R

March 27, 2015
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Using closures as objects in R

For more and more clients we have been using a nice coding pattern taught to us by Garrett Grolemund in his book Hands-On Programming with R: make a function that returns a list of functions. This turns out to be a classic functional programming techique: use closures to implement objects (terminology we will explain). It … Continue reading...

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Machine Learning in R for beginners

March 25, 2015
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Machine Learning in R for beginners

Introducing: Machine Learning in R Machine learning is a branch in computer science that studies the design of algorithms that can learn. Typical machine learning tasks are concept learning, function learning or “predictive modeling”, clustering and finding predictive patterns. These tasks are learned through available data that were observed through experiences or instructions, for example. The post

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Model Segmentation with Cubist

March 18, 2015
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Model Segmentation with Cubist

Cubist is a tree-based model with a OLS regression attached to each terminal node and is somewhat similar to mob() function in the Party package (https://statcompute.wordpress.com/2014/10/26/model-segmentation-with-recursive-partitioning). Below is a demonstrate of cubist() model with the classic Boston housing data.

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Adopting R for experienced developers

March 14, 2015
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Adopting R for experienced developers

More and more frequently I come across people who express an interest in R, and I thought I would share some advice to help people decide if R is something they should use, as well as some high level advice on getting started. Most of these people are developers with at least few years experience writing code...

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Data Science/Statistics/R @Google

February 27, 2015
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This meetup will be hosted by Google and we’ll have Peter Lipman and Pete Meyer...

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Priors on odds and probability of success

February 22, 2015
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Priors on odds and probability of success

In Bayesian Approaches to Clinical Trials and Health-Care Evaluation (David J. Spiegelhalter, Keith R. Abrams, Jonathan P. Myles) they mention that an non informative prior should be uniform over the range of interest. They combine this with the d...

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