Time Series Analysis using R-Forecast package
Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional
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Demonstra algumas das funcionalidades do pacote R forecast
In today’s blog post, we shall look into time series analysis using R package – forecast. Objective of the post will be explaining the different methods available in forecast package which can be applied while dealing with time series analysis/forecasting.
Tags: data mining, previsão, R-software
Avoiding a common mistake with time series
Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional, materiais para profissionais
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Um caso em q a tendência mascara o resto da série criando correlações elevadas
A basic mantra in statistics and data science is correlation is not causation, meaning that just because two things appear to be related to each other doesn’t mean that one causes the other. This is a lesson worth learning.
If you work with data, throughout your career you’ll probably have to re-learn it several times. But you often see the principle demonstrated with a graph like this:
One line is something like a stock market index, and the other is an (almost certainly) unrelated time series like “Number of times Jennifer Lawrence is mentioned in the media.” The lines look amusingly similar. There is usually a statement like: “Correlation = 0.86”. Recall that a correlation coefficient is between +1 (a perfect linear relationship) and -1 (perfectly inversely related), with zero meaning no linear relationship at all. 0.86 is a high value, demonstrating that the statistical relationship of the two time series is strong.
The correlation passes a statistical test. This is a great example of mistaking correlation for causality, right? Well, no, not really: it’s actually a time series problem analyzed poorly, and a mistake that could have been avoided. You never should have seen this correlation in the first place.
The more basic problem is that the author is comparing two trended time series. The rest of this post will explain what that means, why it’s bad, and how you can avoid it fairly simply. If any of your data involves samples taken over time, and you’re exploring relationships between the series, you’ll want to read on.
Tags: previsão
How and Why: Decorrelate Time Series
Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional, materiais para profissionais
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O problemas das autocorrelações nas séries cronológicas.
When dealing with time series, the first step consists in isolating trends and periodicites. Once this is done, we are left with a normalized time series, and studying the auto-correlation structure is the next step, called model fitting. The purpose is to check whether the underlying data follows some well known stochastic process with a similar auto-correlation structure, such as ARMA processes, using tools such as Box and Jenkins. Once a fit with a specific model is found, model parameters can be estimated and used to make predictions.
A deeper investigation consists in isolating the auto-correlations to see whether the remaining values, once decorrelated, behave like white noise, or not. If departure from white noise is found (using a few tests of randomness), then it means that the time series in question exhibits unusual patterns not explained by trends, seasonality or auto correlations. This can be useful knowledge in some contexts such as high frequency trading, random number generation, cryptography or cyber-security. The analysis of decorrelated residuals can also help identify change points and instances of slope changes in time series, or reveal otherwise undetected outliers.
Tags: previsão
Time Series Forecasting and Internet of Things (IoT) in Grain Storage
Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional
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Aplicações reais de previsão com séries cronológicas
Grain storage operators are always trying to minimize the cost of their supply chain. Understanding relationship between receival, outturn, within storage site and between storage site movements can provide us insights that can be useful in planning for the next harvest reason, estimating the throughput capacity of the system, relationship between throughout and inventory. This article explores the potential of scanner data in advance analytics. Combination of these two fields has the potential to be useful for grain storage business. The study describes Grain storage scenarios in the Australian context.
Tags: previsão
Data Analysis Method: Mathematics Optimization to Build Decision Making
Posted by Armando Brito Mendes | Filed under Investigação Operacional, matemática, SAD - DSS
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Uma pequena introdução à utilização de otimização na análise de dados
Optimization is a problem associated with the best decision that is effective and efficient decisions whether it is worth maximum or minimum by way of determining a satisfactory solution.
Optimization is not a new science. It has grown even since Newton in the 17th century discovered how to count roots. Currently the science of optimization is still evolving in terms of techniques and applications. Many cases or problems in everyday life that involve optimization to solve them. Lately much developed especially in the emergence of new techniques to solve the problem of optimization. To mention some, among others, conic programming, semi definite programming, semi infinite programming and some meta heuristic techniques.
Tags: análise de dados, data mining, otimização
Statistical Associates E-Book Catalog
Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional, matemática, materiais ensino
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e-books grátis.
| TITLE | INFO | DESCRIPTION | EDITION | FREE | KINDLE |
| NO PASSWORD REQUIRED FOR TITLES IN THIS SECTION | |||||
| 2013 Annual Report, Statistical Associates Publishers | Info | Pages: 8. Coverage: General. | 2013 | Free | No Kindle edition |
 10 Worst Statistical Mistakes and Pitfalls |
Info | Coverage: For selected statistical procedures | 2015 | Free | No Kindle edition |
| Creating Simulated Datasets | Info | Pages: 15. Coverage: General, SPSS. | 2012 | Free | No Kindle edition |
| Game Theory | Info | Pages: 15. Coverage: General. | 2012 | Free | No Kindle edition |
| Probability | Info | Pages: 15. Coverage: General, SPSS, SAS, Stata. | 2013 | Free | No Kindle edition |
| Testing Statistical Assumptions | Info | Pages: 51. Coverage: General, SPSS. | 2012 | Free | Coming |
| E-MONOGRAPHS: ALL $5 AT AMAZON/KINDLE | |||||
| Association, Measures of | Info | Pages: 49. Coverage: General, SPSS. | 2012 | Free | Buy at Amazon |
| Correlation | Info | Pages: 60. Coverage: General, SPSS, SAS, Stata. | 2013 | Free | Buy at Amazon |
| Correspondence Analysis | Info | Pages: 37. Coverage: General, SPSS. | 2012 | Free | Buy at Amazon |
| Crosstabulation | Info | Pages: 60. Coverage: General, SPSS, SAS, Stata. | 2013 | Free | Buy at Amazon |
| Curve Fitting & Nonlinear Regression | Info | Pages: 53. Coverage: General, SPSS. | 2012 | Free | Buy at Amazon |
| Discriminant Function Analysis | Info | Pages: 52. Coverage: General, SPSS. | 2012 | Free | Buy at Amazon |
| Life Tables & Kaplan-Meier Analysis | Info | Pages: 32. Coverage: General, SPSS. | 2012 | Free | Buy at Amazon |
| Literature Review in Research and Dissertation Writing | Info | Pages: 52. Coverage: General. | 2013 | Free | Buy at Amazon |
| Multidimensional Scaling | Info | Pages: 55. Coverage: General, SPSS. | 2012 | Free | Buy at Amazon |
| Network Analysis | Info | Pages: 35. Coverage: General, UCINET. | 2012 | Free | Buy at Amazon |
| Ordinal Regression | Info | Pages: 93. Coverage: General, SPSS, SAS, Stata. | 2014 | Free | Buy at Amazon |
| Parametric Survival Analysis (Event History Analysis) | Info | Pages: 64. Coverage: General, Stata, SAS. | 2012 | Free | Buy at Amazon |
| Partial Correlation | Info | Pages: 40. Coverage: General, SPSS, SAS, Stata. | 2014 | Free | Buy at Amazon |
| Path Analysis | Info | Pages: 81. Coverage: General, SPSS AMOS. SAS, Stata. | 2014 | Free | Buy at Amazon |
| Power Analysis | Info | Pages: 36. Coverage: General, SPSS SamplePower, G*Power. | 2012 | Free | Buy at Amazon |
| Probit Regression & Response Models | Info | Pages: 92. Coverage: General, SPSS. | 2012 | Free | Buy at Amazon |
| Research Design | Info | Pages: 53. Coverage: General. | 2013 | Free | Buy at Amazon |
| Scales and Measures | Info | Pages: 91. Coverage: General, SPSS, SAS, Stata, WINSTEPS, jMetric | 2013 | Free | Buy at Amazon |
| Survey Research & Sampling | Info | Pages: 82. Coverage: General. | 2013 | Free | Buy at Amazon |
| Two-Stage Least Squares Regression | Info | Pages: 45. Coverage: General, Stata, SPSS, SAS. | 2013 | Free | Buy at Amazon |
| Variance Components Analysis | Info | Pages: 37. Coverage: General, SPSS, SAS. | 2012 | Free | Buy at Amazon |
| WLS: Weighted Least Squares Regression | Info | Pages: 54. Coverage: General, SPSS, SAS, Stata. | 2013 | Free | |
Tags: data mining, motores de busca
Markov Chains explained visually
Posted by Armando Brito Mendes | Filed under Investigação Operacional, matemática, materiais ensino, visualização
Boa forma de perceber como funcionam as cadeias de Markov
Adding on to their series of graphics to explain statistical concepts, Victor Powell and Lewis Lehe use a set of interactives to describe Markov Chains. Even if you already know what Markov Chains are or use them regularly, you can use the full-screen version to enter your own set of transition probabilities. Then let the simulation run.
Tags: grafos, otimização
IFORS Simulation
Posted by Armando Brito Mendes | Filed under estatística, Investigação Operacional, materiais ensino
Algoritmos e Problemas de Simulação
The following 6 pages are in this category, out of 6 total.
D
E
M
S
T
Tags: otimização, software de otimização
IFORS Queueing_Theory
Posted by Armando Brito Mendes | Filed under Investigação Operacional, materiais ensino
Algoritmos e Problemas Filas de Espera
The following 14 pages are in this category, out of 14 total.
Tags: otimização, software de otimização
IFORS Network_Flow_Problems
Posted by Armando Brito Mendes | Filed under Investigação Operacional, materiais ensino, planeamento
Algoritmos e Problemas de Redes
The following 10 pages are in this category, out of 10 total.
ACFG |
IMN |
N cont.T |
Tags: grafos, otimização, software de otimização
