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Stochastic Factors (stochastic + factor)

Distribution by Scientific Domains

Life Sciences	60%

Selected Abstracts

Measurement error and estimates of population extinction risk

ECOLOGY LETTERS, Issue 1 2004
John M. McNamara
Abstract It is common to estimate the extinction probability for a vulnerable population using methods that are based on the mean and variance of the long-term population growth rate. The numerical values of these two parameters are estimated from time series of population censuses. However, the proportion of a population that is registered at each census is typically not constant but will vary among years because of stochastic factors such as weather conditions at the time of sampling. Here, we analyse how such sampling errors influence estimates of extinction risk and find sampling errors to produce two opposite effects. Measurement errors lead to an exaggerated overall variance, but also introduce negative autocorrelations in the time series (which means that estimates of annual growth rates tend to alternate in size). If time series data are treated properly these two effects exactly counter balance. We advocate routinely incorporating a measure of among year correlations in estimating population extinction risk. [source]

Generalized multi-organ autoimmunity in CCR7-deficient mice

EUROPEAN JOURNAL OF IMMUNOLOGY, Issue 3 2007

Abstract Development of autoimmunity is a multi-factorial process involving genetic predisposition as well as environmental and stochastic factors. Although the mechanisms responsible for the initiation of autoimmunity remain only partially understood, several studies have demonstrated that genetic predisposition plays a major role in this process. In the present study, we analyzed the influence of CCR7 signaling in the development of autoimmunity, because this chemokine receptor is essentially involved in the functional organization of thymus architecture. We demonstrate that CCR7-deficient mice are prone to develop generalized multi-organ autoimmunity. The autoimmune phenotype of CCR7,/, mice encompasses the presence of lymphocyte infiltrates in several peripheral organs, circulating autoantibodies against a multitude of tissue-specific antigens and IgG deposition on renal glomeruli. Additionally, CCR7-deficient mice show increased susceptibility to streptozotocin-induced diabetes and spontaneously display signs of chronic autoimmune renal disease. Thus, this study identifies CCR7 as a genetic factor involved in the regulation of autoimmunity. [source]

Somatic NF1 mutation spectra in a family with neurofibromatosis type 1: Toward a theory of genetic modifiers,

HUMAN MUTATION, Issue 6 2003
Verena Wiest
Abstract Neurofibromatosis type 1 (NF1), an autosomal dominantly-inherited disorder, is mainly characterized by the occurrence of multiple dermal neurofibromas and is caused by mutations in the NF1 gene, a tumor suppressor gene. The variable expressivity of the disease and the lack of a genotype/phenotype correlation prevents any prediction of patient outcome and points to the action of genetic factors in addition to stochastic factors modifying the severity of the disease. The analysis of somatic NF1 gene mutations in neurofibromas from NF1 patients revealed that each neurofibroma results from an individual second hit mutation, indicating that factors that influence somatic mutation rates may be regarded as potential modifiers of NF1. A mutational screen of numerous neurofibromas from two NF1 patients presented here revealed a predominance of point mutations, small deletions, and insertions as second hit mutations in both patients. Seven novel mutations are reported. Together with the results of studies that showed LOH as the predominant second hit in neurofibromas of other patients, our results suggest that in different patients different factors may influence the somatic mutation rate and thereby the severity of the disease. Hum Mutat 22:423,427, 2003. © 2003 Wiley-Liss, Inc. [source]

A fractal forecasting model for financial time series

JOURNAL OF FORECASTING, Issue 8 2004
Gordon R. Richards
Abstract Financial market time series exhibit high degrees of non-linear variability, and frequently have fractal properties. When the fractal dimension of a time series is non-integer, this is associated with two features: (1) inhomogeneity,extreme fluctuations at irregular intervals, and (2) scaling symmetries,proportionality relationships between fluctuations over different separation distances. In multivariate systems such as financial markets, fractality is stochastic rather than deterministic, and generally originates as a result of multiplicative interactions. Volatility diffusion models with multiple stochastic factors can generate fractal structures. In some cases, such as exchange rates, the underlying structural equation also gives rise to fractality. Fractal principles can be used to develop forecasting algorithms. The forecasting method that yields the best results here is the state transition-fitted residual scale ratio (ST-FRSR) model. A state transition model is used to predict the conditional probability of extreme events. Ratios of rates of change at proximate separation distances are used to parameterize the scaling symmetries. Forecasting experiments are run using intraday exchange rate futures contracts measured at 15-minute intervals. The overall forecast error is reduced on average by up to 7% and in one instance by nearly a quarter. However, the forecast error during the outlying events is reduced by 39% to 57%. The ST-FRSR reduces the predictive error primarily by capturing extreme fluctuations more accurately. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Seed mass and seedling establishment after fire in Ku-ring-gai Chase National Park, Sydney, Australia

AUSTRAL ECOLOGY, Issue 4 2004
ANGELA T. MOLES
Abstract Relationships between seed mass and several aspects of plant regeneration ecology were investigated in a post-fire environment in Ku-ring-gai Chase National Park near Sydney, Australia. We found a significant positive relationship between seed mass and time to seedling emergence (P < 0.001) and a strong negative relationship between seed mass and time between emergence and production of the first true leaf (P < 0.001). Surprisingly, we found no relationship between seed mass and seedling establishment (P = 0.21). It seems most likely that this lack of relationship is a result of the many stochastic factors affecting seedling establishment during any given recruitment episode at any given site. A cause of mortality was assigned to 56% of the 781 seedlings that died during the present study. There was no relationship between cause of death and seed mass (P = 0.28). Of the seedlings for which the cause of death was known, 57% were killed by herbivory and 21% were killed by drought. Seedling,seedling competition affected only one species. [source]