1537 search results for "regression"

Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks.

June 13, 2012
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Estimation of hydraulic conductivity and its uncertainty from grain-size data using GLUE and artificial neural networks.

AbstractVarious approaches exist to relate saturated hydraulic conductivity (Ks) to grain-size data. Most methods use a single grain-size parameter and hence omit the information encompassed by the entire grain-size distribution. This study compares two data-driven modelling methods—multiple linear regression and artificial neural networks—that use the entire grain-size distribution data as input for Ks prediction. Besides the predictive capacity of the methods,...

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Why R is Hard to Learn

June 13, 2012
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Why R is Hard to Learn

The open source R software for analytics has a reputation for being hard to learn. It certainly can be, especially for people who are already familiar with similar packages such as SAS, SPSS or Stata. Training and documentation that leverages … Continue reading →

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Data distillation with Hadoop and R

June 11, 2012
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Data distillation with Hadoop and R

We're definitely in the age of Big Data: today, there are many more sources of data readily available to us to analyze than there were even a couple of years ago. But what about extracting useful information from novel data streams that are often noisy and minutely transactional ... aye, there's the rub. One of the great things about...

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Autoplot: Graphical Methods with ggplot2

June 11, 2012
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Autoplot:  Graphical Methods with ggplot2

Background As of ggplot2 0.9.0 released in March 2012, there is a new generic function autoplot.  This uses R's S3 methods (which is essentially oop for babies) to let you have some simple overloading of functions.  I'm not going to get deep into oop, because honestly we don't need to. The idea is very simple.  If I say "I'm...

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Classifying the UCI mushrooms

In my last post, I considered the shifts in two interestingness measures as possible tools for selecting variables in classification problems.  Specifically, I considered the Gini and Shannon interestingness measures applied to the 22 categorical mushroom characteristics from the UCI mushroom dataset.  The proposed variable selection strategy was to compare these values when computed from only edible mushrooms...

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R, the master troll of statistical languages

June 8, 2012
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R, the master troll of statistical languages

Warning: what follows is a somewhat technical discussion of my love-hate relationship with the R statistical language, in which I somehow manage to waste 2,400 words talking about a single line of code. Reader discretion is advised. I’ve been using R to do most of my statistical analysis for about 7 or 8 years now–ever

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Simulation in the profiling model

June 7, 2012
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Simulation in the profiling model

In this post I try to make a small simulation of the sensory (flavour) profiling data, and examine if the parameters of simulated data can be retrieved by the Bayesian model build in the previous posts.The conclusion is that it is difficult, the amount...

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Simulating the Birthday Problem with data derived probabilities

June 6, 2012
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Simulating the Birthday Problem with data derived probabilities

You've probably heard of the Birthday Paradox: it only takes a small gathering of people before it's quite likely that two of them share the same birthday. You can solve the problem analytically or with simulation, but usually in either case simplifying assumptions are made (no-one born on February 29, for example). Joe Rickert uses Revolution R Enterprise 6...

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Let’s Party!

June 6, 2012
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Let’s Party!

Exploring whether regression coefficients differ between groups is an important part of applied econometric research, and particularly for research with a policy based objective. For example, a government in a developing country may decide to introduce free school lunches in an effort to improve childhood health. However, if this treatment is known to only improve

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Facts About R Packages (1)

June 6, 2012
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R Packages growth Curve Why R is so popular? There are a lot of reasons, such as: easy to learn and convenient to use, active community, open source, etc. Another important reason is the numerous contributed packages. Up to yesterday, there are 3854 R packages on CRAN. The following figure shows the growth curve of R package: