1960 search results for "Time series"

Plotting Time Series in R using Yahoo Finance data

August 27, 2015
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Plotting Time Series in R using Yahoo Finance data

by Joseph Rickert I recently rediscovered the Timely Portfolio post on R Financial Time Series Plotting. If you are not familiar with this gem, it is well-worth the time to stop and have a look at it now. Not only does it contain some useful examples of time series plots mixing different combinations of time series packages (ts, zoo,...

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Time Series Analysis: Building a model on non-stationary time series

August 15, 2015
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Time Series Analysis: Building a model on non-stationary time series

In this post I will give a brief introduction to time series analysis and its applications. We will be using the R package astsa which was developed by professor David Stoffer at the University of Pittsburgh. The textbook it accompanies, which is a good read for anyone interested in the topic, can be found in

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Time series outlier detection (a simple R function)

July 8, 2015
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Time series outlier detection (a simple R function)

(By Andrea Venturini) Imagine you have a lot of time series – they may be short ones – related to a lot of different measures and very little time to find outliers. You need something not too sophisticated to solve quickly the mess. This is – very shortly speaking – the typical situation in which you can adopt washer.AV()...

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R financial time series tips everyone should know about

July 7, 2015
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There are many R time series tutorials floating around on the web this post is not designed to be one of them. Instead I want to introduce a list of the most useful tricks I came across when dealing with financial time series in R. Some of the functions presented here are incredibly powerful but unfortunately buried in the

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Intraday time series analysis of the #rstats hashtag on Twitter

June 11, 2015
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Intraday time series analysis of the #rstats hashtag on Twitter

This post is a lecture for IS624 Predictive Analytics, which is part of the CUNY Master’s program in Data Analytics. …Continue reading →

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A new R package for detecting unusual time series

May 30, 2015
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A new R package for detecting unusual time series

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

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Copulas and Financial Time Series

May 12, 2015
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Copulas and Financial Time Series

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....

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Time Series Graphs & Eleven Stunning Ways You Can Use Them

April 22, 2015
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Time Series Graphs & Eleven Stunning Ways You Can Use Them

Many graphs use a time series, meaning they measure events over time. William Playfair (1759 - 1823) was a Scottish economist and pioneer of this approach. Playfair invented the line graph. The graph below–one of his most famous–depicts ho...

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Interactive time series with dygraphs

April 14, 2015
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Interactive time series with dygraphs

The dygraphs package is an R interface to the dygraphs JavaScript charting library. It provides rich facilities for charting time-series data in R, including: Automatically plots xts time-series objects (or objects convertible to xts). Rich interactive features including zoom/pan and series/point highlighting. Highly configurable axis and series display (including optional 2nd Y-axis). Display upper/lower bars (e.g. prediction

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Mixing Numbers and Symbols in Time Series Charts

April 8, 2015
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Mixing Numbers and Symbols in Time Series Charts

One of the things I’ve been trying to explore with my #f1datajunkie projects are ways of representing information that work both in a glanceable way as well as repaying deeper reading. I’ve also been looking at various ways of using text labels rather than markers to provide additional information around particular data points. For example,

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