Some of the history of soccer/world football in China is presented. Then consideration turns to the 2008 Chinese Super League. It has 16 teams. The results from the first half of the season, i.e. 15 rounds, are studie...Some of the history of soccer/world football in China is presented. Then consideration turns to the 2008 Chinese Super League. It has 16 teams. The results from the first half of the season, i.e. 15 rounds, are studied. The response of interest for a specific game is whether the home team won, tied or lost, who the home team was, and who the opponent was. The response is ordinal-valued. A generalized linear model is fit and then, given the remaining fixtures, used to predict the final standings of the season. Other explanatories, such as round number, are considered for inclusion in the model. Simulation is employed to estimate probabilities of interest.展开更多
The study of the rodent fluctuations of the North was initiated in its modern form with Elton's pioneering work.Many scientific studies have been designed to collect yearly rodent abundance data,but the resulting ...The study of the rodent fluctuations of the North was initiated in its modern form with Elton's pioneering work.Many scientific studies have been designed to collect yearly rodent abundance data,but the resulting time series are generally subject to at least two "problems":being short and non-linear.We explore the use of the continuous threshold autoregressive(TAR) models for analyzing such data.In the simplest case,the continuous TAR models are additive autoregressive models,being piecewise linear in one lag,and linear in all other lags.The location of the slope change is called the threshold parameter.The continuous TAR models for rodent abundance data can be derived from a general prey-predator model under some simplifying assumptions.The lag in which the threshold is located sheds important insights on the structure of the prey-predator system.We propose to assess the uncertainty on the location of the threshold via a new bootstrap called the nearest block bootstrap(NBB) which combines the methods of moving block bootstrap and the nearest neighbor bootstrap.The NBB assumes an underlying finite-order time-homogeneous Markov process.Essentially,the NBB bootstraps blocks of random block sizes,with each block being drawn from a non-parametric estimate of the future distribution given the realized past bootstrap series.We illustrate the methods by simulations and on a particular rodent abundance time series from Kilpisjrvi,Northern Finland.展开更多
基金supported by US National Science Foundation (Grant No. DMS-0707157)
文摘Some of the history of soccer/world football in China is presented. Then consideration turns to the 2008 Chinese Super League. It has 16 teams. The results from the first half of the season, i.e. 15 rounds, are studied. The response of interest for a specific game is whether the home team won, tied or lost, who the home team was, and who the opponent was. The response is ordinal-valued. A generalized linear model is fit and then, given the remaining fixtures, used to predict the final standings of the season. Other explanatories, such as round number, are considered for inclusion in the model. Simulation is employed to estimate probabilities of interest.
基金supported by US National Science Foundation (Grant No. CMG-0620789)the Research GrantsCouncil of Hong Kong (Grant No. HKU7036/068)the Engineering and Physical Sciences Research Councilof UK (Grant No. EP/C549058/1)
文摘The study of the rodent fluctuations of the North was initiated in its modern form with Elton's pioneering work.Many scientific studies have been designed to collect yearly rodent abundance data,but the resulting time series are generally subject to at least two "problems":being short and non-linear.We explore the use of the continuous threshold autoregressive(TAR) models for analyzing such data.In the simplest case,the continuous TAR models are additive autoregressive models,being piecewise linear in one lag,and linear in all other lags.The location of the slope change is called the threshold parameter.The continuous TAR models for rodent abundance data can be derived from a general prey-predator model under some simplifying assumptions.The lag in which the threshold is located sheds important insights on the structure of the prey-predator system.We propose to assess the uncertainty on the location of the threshold via a new bootstrap called the nearest block bootstrap(NBB) which combines the methods of moving block bootstrap and the nearest neighbor bootstrap.The NBB assumes an underlying finite-order time-homogeneous Markov process.Essentially,the NBB bootstraps blocks of random block sizes,with each block being drawn from a non-parametric estimate of the future distribution given the realized past bootstrap series.We illustrate the methods by simulations and on a particular rodent abundance time series from Kilpisjrvi,Northern Finland.
