Time series decomposition works by splitting a time series into three components: seasonality, trends and random fluctiation. To show how this works, we will study the decompose( ) and STL( ) functions in the R language.
Posted by Armando Brito Mendes | Filed under estatística
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Bom texto com conclusões exclusivas
1. Re-sampling and Statistical Inference
- Main Result
- Sampling with or without Replacement
- Illustration
- Optimum Sample Size
- Optimum K in K-fold Cross-Validation
- Confidence Intervals, Tests of Hypotheses
2. Generic, All-purposes Algorithm
- Re-sampling Algorithm with Source Code
- Alternative Algorithm
- Using a Good Random Number Generator
3. Applications
- A Challenging Data Set
- Results and Excel Spreadsheet
- A New Fundamental Statistics Theorem
- Some Statistical Magic
- How does this work?
- Does this contradict entropy principles?
4. Conclusions
Tags: data mining, inferência, machine learning
Map of Best Breweries in America
Posted by Armando Brito Mendes | Filed under Investigação Operacional, mapas SIG's, visualização
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Um mapa com as melhores produtoras de cerveja artesanal nos EUA e uma rota otimizada com algoritmos genéticos
RateBeer puts out a list every year for top 100 breweries in the world. The rankings are based on reviews, range across styles, and historical performance (and maybe a bit of subjectivity). RateBeer just published the list for 2018. Here’s a map of the 73 U.S.-based breweries.
Brewery Road Trip, Optimized With Genetic Algorithm
Now that we know where they are, let’s find out how to visit all of them in one go.
Tags: belo, grafos, mapas, otimização, R-software, SIG
Eurostat – Eurpean Statistics
Posted by Armando Brito Mendes | Filed under data sets, estatística
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Weather Underground
Posted by Armando Brito Mendes | Filed under data sets
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Fonte de dados sobre o tempo.
Historical Weather
Extracting Seasonality and Trend from Data: Decomposition Using R
Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional, lições, linguagens de programação, materiais ensino, materiais para profissionais
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Uma excelente descrição da decomposição clássica com Python e R.
Understanding Decomposition
Decompose One Time Series into Multiple Series
Time series decomposition is a mathematical procedure which transforms a time series into multiple different time series. The original time series is often split into 3 component series:
- Seasonal: Patterns that repeat with a fixed period of time. For example, a website might receive more visits during weekends; this would produce data with a seasonality of 7 days.
- Trend: The underlying trend of the metrics. A website increasing in popularity should show a general trend that goes up.
- Random: Also call “noise”, “irregular” or “remainder,” this is the residuals of the original time series after the seasonal and trend series are removed.
Tags: engenharia, inferência, otimização, previsão
Biased vs Unbiased: Debunking Statistical Myths
Posted by Armando Brito Mendes | Filed under estatística
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Uma reflexão sobre os enviesamentos que usamos na ciência de dados.
Anyone who attended statistical training at the college level has been taught the four rules that you should always abide by, when developing statistical models and predictions:
- You should only use unbiased estimates
- You should use estimates that have minimum variance
- In any optimization problem (for instance to compute an estimate from a maximum likelihood function, or to detect the best, most predictive subset of variables), you should always shoot for a global optimum, not a local one.
- And if you violate any of the above three rules, at least you need to make sure that your estimate, when the number of observations is large, satisfies them.
As a data scientist and ex-statistician, I violate these rules (especially #1 – #3) almost daily. Indeed, that’s part of what makes data science different from statistical science.
Tags: análise de dados, data mining
Voronoi diagram from smooshing paint between glass
Posted by Armando Brito Mendes | Filed under Investigação Operacional, mapas SIG's, matemática, videos
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Uma abordagem original aos diagramas de Voronoi.
Tags: belo, otimização
The list of 2018 visualization lists
Posted by Armando Brito Mendes | Filed under visualização
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Boa e longa lista de todo o tipo de visualizações.
The list of 2018 visualization lists
December 31, 2018
Officially a yearly habit now: the the list of visualization lists. So here is my list of visualisations, charts, graphics, maps, satellite journalism and science photography lists, version 2018.
Stories, Charts and Maps
@FlowingData: Best Data Visualization Projects of 2018
@ReutersGraphics: The Reuters graphics department takes a lookback at a year’s worth of work
@FiveThirtyEight: The 45 Best — And Weirdest — Charts We Made In 2018
@GuardianVisuals: 18 for 2018: a thread of our biggest projects of the year
@SCMPGraphics: 2018 in visuals: South China Morning Post’s infographic highlights
@qz: The best data visualization in 2018, according to data visualization experts
@HackAStory: The 40 best digital stories of 2018 listed for you by Hackastory
@EconDailyCharts: The 2018 Daily Chart advent calendar
@visualisingdata: 6 monthly reviews of the best of data visualisation @ftdata: Charts of the Year 2018: our writers’ picks @WSJGraphics: The Year in Graphics 2018
….
Tags: belo
Making it easier to discover datasets
Posted by Armando Brito Mendes | Filed under Bases de Dados, materiais para profissionais
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Novo recurso da google para identificar conjuntos de dados.
In today’s world, scientists in many disciplines and a growing number of journalists live and breathe data. There are many thousands of data repositories on the web, providing access to millions of datasets; and local and national governments around the world publish their data as well. To enable easy access to this data, we launched Dataset Search, so that scientists, data journalists, data geeks, or anyone else can find the data required for their work and their stories, or simply to satisfy their intellectual curiosity.
Tags: análise de dados
IFORS Developing Countries OR Resources Website
Posted by Armando Brito Mendes | Filed under Investigação Operacional, materiais ensino, SAD - DSS
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