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Trend Functions (trend + function)

Distribution by Scientific Domains
Mathematics and Statistics66%

Selected Abstracts

Agricultural trade in North America: Trade creation, regionalism and regionalisation

AUSTRALIAN JOURNAL OF AGRICULTURAL & RESOURCE ECONOMICS, Issue 3 2003
Dragan Miljkovic
Trade creation in agricultural products is defined as a statistically significant positive break in the trend function of the growth in exports and imports between member countries. The present study attempts to determine the time of any break in the trend of real exports and imports between the Canada,USA Free Trade Agreement (CUSTA) and the North American Free Trade Agreement (NAFTA) member countries for the years 1980:I through 1999:II, and document the scale of the phenomenon. The present study finds trade creation only occurs in USA agricultural exports to Canada because of CUSTA. The results confirm the theory that the regionalism of NAFTA did not lead to regionalisation or an increasing share of intraregional international trade. [source]

Analytical ecological epidemiology: exposure,response relations in spatially stratified time series

ENVIRONMETRICS, Issue 6 2009
Hagen Scherb
Abstract An important task of environmental research is the investigation of a possible causal relationship between exposure and the frequency of a biologic trait. Major industrial accidents provide examples where the exposure status of large populations may change considerably within relatively short time intervals of days or weeks (e.g. Seveso herbicide plant explosion, Chernobyl Nuclear Power Plant catastrophe). Therefore, purely temporal change-points may be tested in time series of appropriate public health indicators (e.g. mortality, morbidity, sex ratio at birth). If, in addition, the spatial contamination is strong and variable enough and can be identified with sufficient precision at the level of regional units (e.g. districts), then a spatial-temporal approach makes sense. This essentially means that a global time trend model is adjusted for region-specific trend functions, allowing for local or global temporal jumps or broken sticks (change-points) at certain points in time. The local jump heights may be tested for associations with local exposure (exposure,response relation), and all other characteristics in the data that vary with locality and in time are automatically accounted for, thus minimizing confounding. Spatial-temporal approaches may help to strengthen the evidence of possible causal relationships. As an example, the human sex ratio at birth in several European countries before and after the Chernobyl Nuclear Power Plant accident was investigated. A long-term chronic impact of radioactive fallout on the secondary sex ratio has been found. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Emissions of greenhouse gases attributable to the activities of the land transport: modelling and analysis using I-CIR stochastic diffusion,the case of Spain

ENVIRONMETRICS, Issue 2 2008
R. Gutiérrez
Abstract In this study, carried out on the basis of the conclusions and methodological recommendations of the Fourth Assessment Report (2007) of the International Panel on Climate Change (IPCC), we consider the emissions of greenhouse gases (GHG), and particularly those of CO2, attributable to the activities of land transport, for all sectors of the economy, as these constitute a significant proportion of total GHG emissions. In particular, the case of Spain is an example of a worrying situation in this respect, both in itself and in the context of the European Union. To analyse the evolution, in this case, of such emissions, to enable medium-term forecasts to be made and to obtain a model that will enable us to analyse the effects of possible corrector mechanisms, we have statistically fitted a inverse Cox-Ingersoll-Ross (I-CIR) type nonlinear stochastic diffusion process, on the basis of the real data measured for the period 1990,2004, during which the Kyoto protocol has been applicable. We have studied the evolution of the trend of these emissions using estimated trend functions, for which purpose probabilistic complements such as trend functions and stationary distribution are incorporated, and a statistical methodology (estimation and asymptotic inference) for this diffusion, these tools being necessary for the application of the analytical methodology proposed. Copyright © 2007 John Wiley & Sons, Ltd. [source]

A diffusion model with cubic drift: statistical and computational aspects and application to modelling of the global CO2 emission in Spain

ENVIRONMETRICS, Issue 1 2007
R. Gutiérrez
Abstract The aim of this work is the study of a new stochastic diffusion model with a cubic-type drift coefficient. The model is considered as the solution of an Ito stochastic differential equation. Using the Ito's stochastic calculus and properties of the Kummer function, the trend functions and steady-state distribution for the process are obtained. Statistical estimation and corresponding computational methodology are established. Finally, the model is applied to modelling and prediction of the global CO2 emission in Spain. Copyright © 2006 John Wiley & Sons, Ltd. [source]

Modelling current trends in Northern Hemisphere temperatures

INTERNATIONAL JOURNAL OF CLIMATOLOGY, Issue 7 2006
Terence C. Mills
Abstract Fitting a trend is of interest in many disciplines, but it is of particular importance in climatology, where estimating the current and recent trend in temperature is thought to provide a major indication of the presence of global warming. A range of ad hoc methods of trend fitting have been proposed, with little consensus as to the most appropriate techniques to use. The aim of this paper is to consider a range of trend extraction techniques, none of which require ,padding' out the series beyond the end of the available observations, and to use these to estimate the trend of annual mean Northern Hemisphere (NH) temperatures. A comparison of the trends estimated by these methods thus provides a robust indication of the likely range of current trend temperature increases and hence inform, in a timely quantitative fashion, arguments based on global temperature data concerning the nature and extent of global warming and climate change. For the complete sample 1856,2003, the trend is characterised as having long waves about an underlying increasing level. Since around 1970, all techniques display a pronounced warming trend. However, they also provide a range of trend functions so that extrapolation far into the future would be a hazardous exercise. Copyright © 2006 Royal Meteorological Society. [source]

Modelling and forecasting vehicle stocks using the trends of stochastic Gompertz diffusion models: The case of Spain

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 3 2009
R. Gutiérrez
Abstract In the present study, we treat the stochastic homogeneous Gompertz diffusion process (SHGDP) by the approach of the Kolmogorov equation. Firstly, using a transformation in diffusion processes, we show that the probability transition density function of this process has a lognormal time-dependent distribution, from which the trend and conditional trend functions and the stationary distribution are obtained. Second, the maximum likelihood approach is adapted to the problem of parameters estimation in the drift and the diffusion coefficient using discrete sampling of the process, then the approximated asymptotic confidence intervals of the parameter are obtained. Later, we obtain the corresponding inference of the stochastic homogeneous lognormal diffusion process as limit from the inference of SHGDP when the deceleration factor tends to zero. A statistical methodology, based on the above results, is proposed for trend analysis. Such a methodology is applied to modelling and forecasting vehicle stocks. Finally, an application is given to illustrate the methodology presented using real data, concretely the total vehicle stocks in Spain. Copyright © 2008 John Wiley & Sons, Ltd. [source]