# 1129 search results for "latex"

## A new R package for detecting unusual time series

May 30, 2015
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The anomalous package provides some tools to detect unusual time series in a large collection of time series. This is joint work with Earo Wang (an honours student at Monash) and Nikolay Laptev (from Yahoo Labs). Yahoo is interested in detecting unusual patterns in server metrics. The basic idea is to measure a range of

May 26, 2015
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Another trip in the métro today (to work with Pierre Jacob and Lawrence Murray in a Paris Anticafé!, as the University was closed) led me to infer—warning!, this is not the exact distribution!—the distribution of x, namely since a path x of length l(x) will corresponds to N draws if N-l(x) is an even integer

## Simulation-based power analysis using proportional odds logistic regression

May 22, 2015
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Consider planning a clinicial trial where patients are randomized in permuted blocks of size four to either a 'control' or 'treatment' group. The outcome is measured on an 11-point ordinal scale (e.g., the numerical rating scale for pain). It may be reasonable to evaluate the results of this trial using a proportional odds cumulative logit

## Introductory Point Pattern Analysis of Open Crime Data in London

May 21, 2015
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IntroductionPolice in Britain (http://data.police.uk/) not only register every single crime they encounter, and include coordinates, but also distribute their data free on the web.They have two ways of distributing data: the first is through an API, which is extremely easy to use but returns only a limited number of crimes for each request, the second is...

## Analyzing R-Bloggers’ posts via Twitter

May 18, 2015
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For those who don’t know, every time a new blog post gets added to R-Bloggers, it gets a corresponding tweet by @Rbloggers, which gets seen by Rbloggers’ ~20k followers fairly fast. And every time my post gets published, I can’t help but check up on how many people gave that tweet some Twitter love, ie. “favorite”d or...

## Recent Common Ancestors: Simple Model

May 15, 2015
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An interesting paper (Modelling the recent common ancestry of all living humans, Nature, 431, 562–566, 2004) by Rohde, Olson and Chang concludes with the words: Further work is needed to determine the effect of this common ancestry on patterns of genetic variation in structured populations. But to the extent that ancestry is considered in genealogical The post

## Copulas and Financial Time Series

May 12, 2015
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I was recently asked to write a survey on copulas for financial time series. The paper is, so far, unfortunately, in French, and is available on https://hal.archives-ouvertes.fr/. There is a description of various models, including some graphs and statistical outputs, obtained from read data. To illustrate, I’ve been using weekly log-returns of (crude) oil prices, Brent, Dubaï and Maya....

## Survival Analysis With Generalized Additive Models: Part V (stratified baseline hazards)

May 9, 2015
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$Survival Analysis With Generalized Additive Models: Part V (stratified baseline hazards)$

In the fifth part of this series we will examine the capabilities of Poisson GAMs to stratify the baseline hazard for survival analysis. In a stratified Cox model, the baseline hazard is not the same for all individuals in the study. Rather, it is assumed that the baseline hazard may differ between members of groups, even though it will

## Survival Analysis With Generalized Additive Models : Part IV (the survival function)

May 2, 2015
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$Survival Analysis With Generalized Additive Models : Part IV (the survival function)$

The ability of PGAMs to estimate the log-baseline hazard rate, endows them with the capability to be used as smooth alternatives to the Kaplan Meier curve. If we assume for the shake of simplicity that there are no proportional co-variates in the PGAM regression, then the quantity modeled  corresponds to the log-hazard of the  survival

## Survival Analysis With Generalized Additive Models : Part III (the baseline hazard)

May 2, 2015
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$Survival Analysis With Generalized Additive Models : Part III (the baseline hazard)$

In the third part of the series on survival analysis with GAMs we will review the use of the baseline hazard estimates provided by this regression model. In contrast to the Cox mode, the log-baseline hazard is estimated along with other quantities (e.g. the log hazard ratios) by the Poisson GAM (PGAM) as: In the