1616 search results for "regression"

Dynamic Modeling 2: Our First Substantive Model

May 30, 2010
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Dynamic Modeling 2: Our First Substantive Model

(This is the second of a series of ongoing posts on using Graph Algebra in the Social Sciences.) First-order linear difference equations are powerful, yet simple modeling tools.  They can provide access to useful substantive insights to real-world phenomena.  They can have powerful predictive ability when used appropriately.  Additionally, they may be classified in any number

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Dynamic Modeling 1: Linear Difference Equations

May 28, 2010
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Dynamic Modeling 1: Linear Difference Equations

(This is the first in a series on the use of Graph Algebraic models for Social Science.) Linear Difference models are a hugely important first step in learning Graph Algebraic modeling.  That said, linear difference equations are a completely independent thing from Graph Algebra.  I’ll get into the Graph algebra stuff in the next post or

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Voter targeting with R

May 26, 2010
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Voter targeting with R

Voter targeting for turnout is the process of scoring registered voters using demographic and electoral variables taken from voter lists and commercial databases. The score of all voters together is used to predict overall turnout, which determines the allocation of campaign resources and directs strategy for voter contact and communication. Targeting for turnout is a

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The Kalman Filter For Financial Time Series

May 25, 2010
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The Kalman Filter For Financial Time Series

Every now and then I come across a tool that is so bogged down in pages of esoteric mathematical calculations, it becomes difficult to get even a simple grasp of how or why they might be useful. Even worse, you exhaustively search the internet to find ...

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extrapolation and interpolation The most important lesson I…

May 25, 2010
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extrapolation and interpolation
The most important lesson I…

extrapolation and interpolation The most important lesson I learned from this book:  regression is reliable for interpolation, but not for extrapolation.  Even further, your observations really need to cover the whole gamut of causal variables, inter...

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RcppArmadillo 0.2.1

May 19, 2010
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Armadillo Armadillo is a C++ linear algebra library aiming towards a good balance between speed and ease of use. Integer, floating point and complex numbers are supported, as well as a subset of trigonometric and statistics functions. Various matr...

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Confusing slice sampler

May 18, 2010
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Confusing slice sampler

Most embarrassingly, Liaosa Xu from Virginia Tech sent the following email almost a month ago and I forgot to reply: I have a question regarding your example 7.11 in your book Introducing Monte Carlo Methods with R.  To further decompose the uniform simulation by sampling a and b step by step, how you determine the

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Winning the first game in a baseball series: a harbinger, or not?

May 17, 2010
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Winning the first game in a baseball series: a harbinger, or not?

For those not familiar with the major-league baseball in the US (and despite living here for more than 10 years, I still include myself in that category), the games usually played in series: team A visits the home of team B, and the two teams play two or more games against each other on successive days. It's common wisdom...

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Index of the R-Sessions

May 17, 2010
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The R-Sessions are a series of blog entries on using R. A large part consists of an R-manual I once wrote. Other posts include some tricks I found out, as well as entries detailing functions and packages I wrote for ...

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Manual variable selection using the dropterm function

May 12, 2010
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Manual variable selection using the dropterm function

When fitting a multiple linear regression model to data a natural question is whether a model can be simplified by excluding variables from the model. There are automatic procedures for undertaking these tests but some people prefer to follow a more manual approach to variable selection rather than pressing a button and taking what comes

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