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Successive Observations (successive + observation)

Distribution by Scientific Domains

Life Sciences	40%

Selected Abstracts

The Effects of Random and Discrete Sampling when Estimating Continuous,Time Diffusions

ECONOMETRICA, Issue 2 2003
Sahalia, Yacine Aït
High,frequency financial data are not only discretely sampled in time but the time separating successive observations is often random. We analyze the consequences of this dual feature of the data when estimating a continuous,time model. In particular, we measure the additional effects of the randomness of the sampling intervals over and beyond those due to the discreteness of the data. We also examine the effect of simply ignoring the sampling randomness. We find that in many situations the randomness of the sampling has a larger impact than the discreteness of the data. [source]

Allowing for redundancy and environmental effects in estimates of home range utilization distributions

ENVIRONMETRICS, Issue 1 2005
W. G. S. Hines
Abstract Real location data for radio tagged animals can be challenging to analyze. They can be somewhat redundant, since successive observations of an animal slowly wandering through its environment may well show very similar locations. The data set can possess trends over time or be irregularly timed, and they can report locations in environments with features that should be incorporated to some degree. Also, the periods of observation may be too short to provide reliable estimates of characteristics such as inter-observation correlation levels that can be used in conventional time-series analyses. Moreover, stationarity (in the sense of the data being generated by a source that provides observations of constant mean, variance and correlation structure) may not be present. This article considers an adaptation of the kernel density estimator for estimating home ranges, an adaptation which allows for these various complications and which works well in the absence of exact (or precise) information about correlation structure and parameters. Modifications to allow for irregularly timed observations, non-stationarity and heterogeneous environments are discussed and illustrated. Copyright © 2004 John Wiley & Sons, Ltd. [source]

Assessment of short-term association between health outcomes and ozone concentrations using a Markov regression model

ENVIRONMETRICS, Issue 3 2003
Abdelkrim Zeghnoun
Abstract Longitudinal binary data are often used in panel studies where short-term associations between air pollutants and respiratory health outcomes are investigated. A Markov regression model in which the transition probabilities depend on the covariates, as well as the past responses, was used to study the short-term association between daily ozone (O3) concentrations and respiratory health outcomes in a panel of schoolchildren in Armentières, Northern France. The results suggest that there was a small but statistically significant association between O3 and children's cough episodes. A 10,,g/m3 increase in O3 concentrations was associated with a 13.9,% increase in cough symptoms (CI,95%,=,1.2,28.1%). The use of a Markov regression model can be useful as it permits one to address easily both the regression objective and the stochastic dependence between successive observations. However, it is important to verify the sensitivity of the Markov regression parameters to the time-dependence structure. In this study, it was found that, although what happened on the previous day was a strong predictor of what happened on the current day, this did not contradict the O3 -respiratory symptom associations. Compared to the Markov regression model, the signs of the parameter estimates of marginal and random-intercept models remain the same. The magnitudes of the O3 effects were also essentially the same in the three models, whose confidence intervals overlapped. Copyright © 2003 John Wiley & Sons, Ltd. [source]

House Finch Carpodacus mexicanus roosting behaviour during the non-breeding season and possible effects of mycoplasmal conjunctivitis

IBIS, Issue 1 2007
ANDRÉ A. DHONDT
We studied House Finch Carpodacus mexicanus roosting behaviour during the non-breeding season using radiotracking and direct observations in Ithaca, NY, USA. In contrast to what has been reported in the literature and in contrast to what should be expected from Newton's European studies of cardueline finches, House Finches roost in small groups (mean 3.5; maximum 11) and do not display at roost sites. Seventy-seven per cent of the birds re-used the same tree on successive observations. In winter, birds re-used the same roost tree more often than in the autumn, and birds with mycoplasmal conjunctivitis tended to move more between roost trees than did birds without conjunctivitis. A small number of radiotagged birds that roosted in the same tree were observed together in the daytime more often than by chance, suggesting the existence of social bonds between birds (some same sex) during the non-breeding season. In the autumn the birds often roosted in leafed deciduous trees and closer to their daytime feeding locations than they did in winter. In winter all birds roosted in evergreen trees. It is possible that the reliable and predictable food sources at feeding sites offered by the public might have changed House Finch roosting behaviour. [source]

Environmental colour intensifies the Moran effect when population dynamics are spatially heterogeneous

OIKOS, Issue 10 2007
David A. Vasseur
Evidence for synchronous fluctuations of spatially separated populations is ubiquitous in the literature, including accounts within and across taxa. Among the few mechanisms explaining this phenomenon is the Moran effect, whereby independent populations are synchronized by spatially correlated environmental disturbances. The body of research on the Moran effect predominantly assumes that environmental disturbances within a local site are serially uncorrelated; that is, successive observations in time at a particular local site are independent. Yet, many environmental variables are known to possess strong temporal autocorrelation , a character which has often been described as ,colour'. The omission of environmental colour from research on the Moran effect may be due in part to the lack of methods capable of generating sets of time series with a desired colour and spatial correlation. Here I present a novel and simple method designated as ,phase partnering' to generate such sets of time series and I investigate the combined impact of spatial correlation and environmental colour on population synchrony in two common models of population dynamics. For linear population dynamics, and for a subset of nonlinear population dynamics, coloured environments intensify the Moran effect when population dynamics are spatially heterogeneous; in coloured environments the spatial correlation between populations more closely mimics the spatial correlation between their respective environments. Given that most environmental variables are coloured, these results imply that the Moran effect may be a far more significant driver of regional-scale population and interspecific synchrony than is currently believed. [source]