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Statistical Methods for Trend Detection and Analysis in the Environmental Sciences Book

Statistical Methods for Trend Detection and Analysis in the Environmental Sciences
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Statistical Methods for Trend Detection and Analysis in the Environmental Sciences, The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monit, Statistical Methods for Trend Detection and Analysis in the Environmental Sciences
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  • Statistical Methods for Trend Detection and Analysis in the Environmental Sciences
  • Written by author Richard Chandler
  • Published by Wiley, John & Sons, Incorporated, 3/25/2011
  • The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monit
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Authors

Preface.

Part I METHODOLOGY.

1 Introduction.
1.1 What is a Trend?
1.2 Why Analyse Trends?
1.3 Some simple examples.
1.4 Considerations and Difficulties.
1.5 Scope of the book.
1.6 Further reading.
References.

2 Exploratory Analysis.
2.1 Data Visualisation.
2.2 Simple smoothing.
2.3 Linear Filters.
2.4 Classical Test Procedures.
2.5 Concluding comments.
References.

3 Parametric Modelling - Deterministic Trends.
3.1 The Linear Trend.
3.2 Multiple Regression Techniques.
3.3 Violations of assumptions.
3.4 Nonlinear Trends.
3.5 Generalized Linear Models.
3.6 Inference with small samples.
References.

4 Nonparametric Trend Estimation.
4.1 An introduction to nonparametric regression.
4.2 Multiple covariates.
4.3 Other Nonparametric Estimation Techniques.
4.4 Parametric or Nonparametric?
References.

5 Stochastic Trends.
5.1 Stationary Time Series Models and their Properties.
5.2 Trend Removal via Differencing.
5.3 Long Memory Models.
5.4 Models for irregularly spaced series.
5.5 State Space and Structural Models.
5.6 Nonlinear models.
References.

6 Other Issues.
6.1 Multisite Data.
6.2 Multivariate series.
6.3 Point Process Data.
6.4 Trends in Extremes.
6.5 Censored Data.
References.

Part II CASE STUDIES.

7 Additive Models for Sulphur Dioxide Pollution in Europe.
7.1 Introduction.
7.2 Additive models with correlated errors.
7.3 Models for the SO2 data.
7.4 Conclusions.
References.

8 Rainfall trends in southwest Western Australia.
8.1 Motivation.
8.2 The study region.
8.3 Data used in the study.
8.4 Modelling methodology.
8.5 Results.
8.6 Summary and conclusions.
References.

9 Additive modelling and dynamic factor analysis to estimate common
trends in trophic index time series from the coastal waters in Emilia-
Romagna (Adriatic Sea - Italy).
9.1 Introduction.
9.2 Data exploration.
9.3 Common trends and additive modelling.
9.4 Dynamic factor analysis to estimate common trends.
9.5 Discussion.
References.

10 A Space-Time Study on Forest Health.
10.1 Forest health: survey and data.
10.2 Regression models for longitudinal data with ordinal responses.
10.3 Spatio-temporal models.
10.4 Spatio-temporal modelling and analysis of forest health data.
References.

Index.


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Statistical Methods for Trend Detection and Analysis in the Environmental Sciences, The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monit, Statistical Methods for Trend Detection and Analysis in the Environmental Sciences

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Statistical Methods for Trend Detection and Analysis in the Environmental Sciences, The need to understand and quantify change is fundamental throughout the environmental sciences. This might involve describing past variation, understanding the mechanisms underlying observed changes, making projections of possible future change, or monit, Statistical Methods for Trend Detection and Analysis in the Environmental Sciences

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