2047 search results for "regression"

Example 2014.11: Contrasts the basic way for R

September 30, 2014
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Example 2014.11: Contrasts the basic way for R

As we discuss in section 6.1.4 of the second edition, R and SAS handle categorical variables and their parameterization in models quite differently. SAS treats them on a procedure-by-procedure basis, which leads to some odd differences in capabilities and default parameterizations. For example, in the logistic procedure, the default is effect cell coding, while in the genmod...

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seeking altruistic social scientists, demographers, survey researchers

September 30, 2014
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seeking altruistic social scientists, demographers, survey researchers

hi everyone, please share this:  if you are an experienced user of a publicly-available survey data set from any country or international organization, let's work together on some user-friendly code and a short blog post for http://asdfree.com.&nb...

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Recognizing Patterns in the Purchase Process by Following the Pathways Marked By Others

September 27, 2014
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Recognizing Patterns in the Purchase Process by Following the Pathways Marked By Others

Herbert Simon's "ant on the beach" does not search for food in a straight line because the environment is not uniform with pebbles, pools and rough terrain. At least the ant's decision making is confined to the 3-dimensional space defining the beach. C...

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Estimating Generalization Error with the PRESS statistic

September 25, 2014
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Estimating Generalization Error with the PRESS statistic

As we’ve mentioned on previous occasions, one of the defining characteristics of data science is the emphasis on the availability of “large” data sets, which we define as “enough data that statistical efficiency is not a concern” (note that a “large” data set need not be “big data,” however you choose to define it). In Related posts:

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DescTools: a new R "misc package"

September 25, 2014
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DescTools: a new R "misc package"

by Joseph Rickert One of the most difficult things about R, a problem that is particularly vexing to beginners, is finding things. This is an unintended consequence of R's spectacular, but mostly uncoordinated, organic growth. The R core team does a superb job of maintaining the stability and growth of the R language itself, but the innovation engine for...

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Joint Models for Longitudinal and Survival Data

September 25, 2014
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Joint Models for Longitudinal and Survival Data

What are joint models for longitudinal and survival data? In this post we will introduce in layman's terms the framework of joint models for longitudinal and time-to-event data. These models are applied in settings where the sample units are followed-up in time, for example, we may be interest in patients suffering...

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Multiple Tests, an Introduction

September 24, 2014
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Multiple Tests, an Introduction

Last week, a student asked me about multiple tests. More precisely, she ran an experience over – say – 20 weeks, with the same cohort of – say – 100 patients. An we observe some size=100 nb=20 set.seed(1) X=matrix(rnorm(size*nb),size,nb) (here, I just generate some fake data). I can visualize some trajectories, over the 20 weeks, library(RColorBrewer) cl1=brewer.pal(12,"Set3") cl2=brewer.pal(8,"Set2") cl=c(cl1,cl2)...

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In-depth introduction to machine learning in 15 hours of expert videos

September 23, 2014
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In-depth introduction to machine learning in 15 hours of expert videos

In January 2014, Stanford University professors Trevor Hastie and Rob Tibshirani (authors of the legendary Elements of Statistical Learning textbook) taught an online course based on their newest textbook, An Introduction to Statistical Learning with Applications in R (ISLR). I found it to be an excellent course in statistical learning (also known as "machine learning"), largely...

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Accelerating the Random Forest Algorithm, I: the Algorithm

September 22, 2014
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The Random Forest algorithm is a well-known tool for data analysis. It yields robust predictive models for vastly different data sets, serving as a sort of Swiss Army Knife in the data scientist's toolkit. Given the need to accommodate ever-larger data sets, scalable...

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Build Predictive Model on Big data: Using R and MySQL Part-3

September 21, 2014
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Build Predictive Model on Big data: Using R and MySQL Part-3

Welcome to last part of the series post again! In previous part I discussed about the solutions to the questions mentioned in first part. In this part, we will implement whole scenario using R and MySQL together and see how we can process bigdata(computationally ) Let us recall those questions and summarize their answers to The post Build...

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