1273 search results for "latex"

Census Open Atlas Project Version Two

February 5, 2014
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Census Open Atlas Project Version Two

This time last year I published the first version of the 2011 Census Open Atlas which comprised Output Area Level census maps for each local authority district. This turned out to be quite a popular project, and I have also extended this to Japan. The methods used to construct the atlases have now been refined,...

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Solutions for Multicollinearity in Regression(1)

February 3, 2014
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Solutions for Multicollinearity in Regression(1)

In multiple regression analysis, multicollinearity is a common phenomenon, in which two or more predictor variables are highly correlated. If there is an exact linear relationship (perfect multicollinearity) among the independent variables, the rank of X is less than k+1(assume the number of predictor variables is k), and the matrix will not be invertible. So the strong correlations … Continue reading...

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Caching API calls offline

February 2, 2014
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I've recently heard the idea of "offline first" via especially Hood.ie. We of course don't do web development, but primarily build R interfaces to data on the web. Internet availablility is increasinghly ubiqutous, but there still are times and places where you don't have internet, but need to get work done. In the R packages we write there...

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Pander/Pandoc for Pretty Conversion on the R Studio Server

February 1, 2014
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Eventually we get around to teaching our students to turn in Homework assignments as R Markdown documents, and towards the end of the semester many of them will do a data analysis project, complete with a report generated as an HTML file. But frankly the HTML output is a bit ugly. What if students want something that looks a...

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Inference for ARMA(p,q) Time Series

January 30, 2014
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Inference for ARMA(p,q) Time Series

As we mentioned in our previous post, as soon as we have a moving average part, inference becomes more complicated. Again, to illustrate, we do not need a two general model. Consider, here, some  process, where  is some white noise, and assume further that . > theta=.7 > phi=.5 > n=1000 > Z=rep(0,n) > set.seed(1) > e=rnorm(n) > for(t...

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Inference for MA(q) Time Series

January 29, 2014
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Inference for MA(q) Time Series

Yesterday, we’ve seen how inference for time series was possible.  I started  with that one because it is actually the simple case. For instance, we can use ordinary least squares. There might be some possible bias (see e.g. White (1961)), but asymptotically, estimators are fine (consistent, with asymptotic normality). But when the noise is (auto)correlated, then it is more...

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Inference for AR(p) Time Series

January 28, 2014
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Inference for AR(p) Time Series

Consider a (stationary) autoregressive process, say of order 2, for some white noise with variance . Here is a code to generate such a process, > phi1=.25 > phi2=.7 > n=1000 > set.seed(1) > e=rnorm(n) > Z=rep(0,n) > for(t in 3:n) Z=phi1*Z+phi2*Z+e > Z=Z > n=length(Z) > plot(Z,type="l") Here, we have to estimate two sets of parameters: the autoregressive...

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cut, baby, cut!

January 28, 2014
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cut, baby, cut!

At MCMSki IV, I attended (and chaired) a session where Martyn Plummer presented some developments on cut models. As I was not sure I had gotten the idea [although this happened to be one of those few sessions where

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Bias of Hill Estimators

January 28, 2014
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Bias of Hill Estimators

In the MAT8595 course, we’ve seen yesterday Hill estimator of the tail index. To be more specific, we did see see that if , with , then Hill estimators for are given by for . Then we did say that satisfies some consistency in the sense that if , but not too fast, i.e. (under additional assumptions on the...

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New in forecast 5.0

January 26, 2014
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New in forecast 5.0

Last week, version 5.0 of the forecast package for R was released. There are a few new functions and changes made to the package, which is why I increased the version number to 5.0. Thanks to Earo Wang for helping with this new version. Handling missing values and outliers Data cleaning is often the first step that data scientists...

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