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Advances in Time Series Analysis and Forecasting

Overview of attention for book
Cover of 'Advances in Time Series Analysis and Forecasting'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Small Crack Fatigue Growth and Detection Modeling with Uncertainty and Acoustic Emission Application
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    Chapter 2 Acanthuridae and Scarinae: Drivers of the Resilience of a Polynesian Coral Reef
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    Chapter 3 Using Time Series Analysis for Estimating the Time Stamp of a Text
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    Chapter 4 Using LDA and Time Series Analysis for Timestamping Documents
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    Chapter 5 Fractal Complexity of the Spanish Index IBEX 35
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    Chapter 6 Fractional Brownian Motion in OHLC Crude Oil Prices
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    Chapter 7 Time-Frequency Representations as Phase Space Reconstruction in Symbolic Recurrence Structure Analysis
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    Chapter 8 Analysis of Climate Dynamics Across a European Transect Using a Multifractal Method
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    Chapter 9 Comparative Analysis of ARMA and GARMA Models in Forecasting
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    Chapter 10 SARMA Time Series for Microscopic Electrical Load Modeling
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    Chapter 11 Diagnostic Checks in Multiple Time Series Modelling
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    Chapter 12 Mixed AR(1) Time Series Models with Marginals Having Approximated Beta Distribution
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    Chapter 13 Prediction of Noisy ARIMA Time Series via Butterworth Digital Filter
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    Chapter 14 Mandelbrot’s 1/f  Fractional Renewal Models of 1963–67: The Non-ergodic Missing Link Between Change Points and Long Range Dependence
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    Chapter 15 Detection of Outlier in Time Series Count Data
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    Chapter 16 Ratio Tests of a Change in Panel Means with Small Fixed Panel Size
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    Chapter 17 Operational Turbidity Forecast Using Both Recurrent and Feed-Forward Based Multilayer Perceptrons
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    Chapter 18 Productivity Convergence Across US States in the Public Sector. An Empirical Study
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    Chapter 19 Proposal of a New Similarity Measure Based on Delay Embedding for Time Series Classification
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    Chapter 20 A Fuzzy Time Series Model with Customized Membership Functions
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    Chapter 21 Model-Independent Analytic Nonlinear Blind Source Separation
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    Chapter 22 Dantzig-Selector Radial Basis Function Learning with Nonconvex Refinement
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    Chapter 23 A Soft Computational Approach to Long Term Forecasting of Failure Rate Curves
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    Chapter 24 A Software Architecture for Enabling Statistical Learning on Big Data
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    Chapter 25 Wind Speed Forecasting for a Large-Scale Measurement Network and Numerical Weather Modeling
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    Chapter 26 Analysis of Time-Series Eye-Tracking Data to Classify and Quantify Reading Ability
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    Chapter 27 Forecasting the Start and End of Pollen Season in Madrid
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    Chapter 28 Statistical Models and Granular Soft RBF Neural Network for Malaysia KLCI Price Index Prediction
Attention for Chapter 14: Mandelbrot’s 1/f  Fractional Renewal Models of 1963–67: The Non-ergodic Missing Link Between Change Points and Long Range Dependence
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Mentioned by

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Chapter title
Mandelbrot’s 1/f  Fractional Renewal Models of 1963–67: The Non-ergodic Missing Link Between Change Points and Long Range Dependence
Chapter number 14
Book title
Advances in Time Series Analysis and Forecasting
Published in
arXiv, June 2016
DOI 10.1007/978-3-319-55789-2_14
Book ISBNs
978-3-31-955788-5, 978-3-31-955789-2
Authors

Nicholas Wynn Watkins

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 50%
Other 1 13%
Student > Ph. D. Student 1 13%
Student > Doctoral Student 1 13%
Student > Master 1 13%
Other 1 13%
Readers by discipline Count As %
Physics and Astronomy 4 50%
Mathematics 1 13%
Computer Science 1 13%
Agricultural and Biological Sciences 1 13%
Neuroscience 1 13%
Other 1 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 March 2016.
All research outputs
#18,148,462
of 23,314,015 outputs
Outputs from arXiv
#449,026
of 960,567 outputs
Outputs of similar age
#254,817
of 353,741 outputs
Outputs of similar age from arXiv
#6,392
of 15,712 outputs
Altmetric has tracked 23,314,015 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 960,567 research outputs from this source. They receive a mean Attention Score of 3.9. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 353,741 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 15,712 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.