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Variance Ratio (variance + ratio)

Distribution by Scientific Domains

Business, Economics, Finance and Accounting	33%

Selected Abstracts

Are ectoparasite communities structured?

JOURNAL OF ANIMAL ECOLOGY, Issue 6 2006
Species co-occurrence, null models, temporal variation
Summary 1We studied temporal variation in the structure of flea communities on small mammalian hosts from eastern Slovakia using null models. We asked (a) whether flea co-occurrences in infracommunities (in the individual hosts) in different hosts as well as in the component communities (in the host species) demonstrate a non-random pattern; (b) whether this pattern is indicative of either positive or negative flea species interactions; (c) whether this pattern varies temporally; and (d) whether the expression of this pattern is related to population size of either fleas or hosts or both. 2We constructed a presence/absence matrix of flea species for each temporal sample of a host species and calculated four metrics of co-occurrence, namely the C -score, the number of checkerboard species pairs, the number of species combinations and the variance ratio (V -ratio). Then we compared these metrics with the respective indices calculated for 5000 null matrices that were assembled randomly using two algorithms, namely fixed-fixed (FF) and fixed-equiprobable (FE). 3Most co-occurrence metrics calculated for real data did not differ significantly from the metrics calculated for simulated matrices using the FF algorithm. However, the indices observed for 42 of 75 presence/absence matrices differed significantly from the null expectations for the FE models. Non-randomness was detected mainly by the C -score and V -ratio metrics. In all cases, the direction of non-randomness was the same, namely the aggregation, not competition, of flea species in host individuals and host species. 4The inclusion or exclusion of the uninfested hosts in the FE models did not affect the results for individual host species. However, exclusion of the uninfested host species led to the acceptance of the null hypothesis for only six of 13 temporal samples of the component flea communities for which non-randomness was detected when the uninfested hosts were included in the analysis. 5In most host species, the absolute values of the standardized size effect of both the C -score and V -ratio increased with an increase in host density and a concomitant decrease in flea abundance and prevalence. 6Results of this study demonstrated that (a) flea assemblages on small mammalian hosts were structured at some times, whereas they appeared to be randomly assembled at other times; (b) whenever non-randomness of flea co-occurrences was detected, it suggested aggregation but never segregation of flea species in host individuals or populations; and (c) the expression of structure in flea assemblages depended on the level of density of both fleas and hosts. [source]

The variance ratio and trend stationary model as extensions of a constrained autoregressive model

JOURNAL OF FORECASTING, Issue 5 2010
Shlomo Zilca
Abstract This paper shows that a constrained autoregressive model that assigns linearly decreasing weights to past observations of a stationary time series has important links to the variance ratio methodology and trend stationary model. It is demonstrated that the proposed autoregressive model is asymptotically related to the variance ratio through the weighting schedules that these two tools use. It is also demonstrated that under a trend stationary time series process the proposed autoregressive model approaches a trend stationary model when the memory of the autoregressive model is increased. These links create a theoretical foundation for tests that confront the random walk model simultaneously against a trend stationary and a variety of short- and long-memory autoregressive alternatives. Copyright © 2009 John Wiley & Sons, Ltd. [source]

Spatial patterns of association at local and regional scales in coastal sand dune communities

JOURNAL OF VEGETATION SCIENCE, Issue 5 2009
Estelle Forey
Abstract Questions: Are positive understorey-dominant associations important in physically severe dune communities and does the strength of positive associations vary with disturbance at the local scale and with stress at the regional scale? Do associational patterns observed at the neighbourhood scale predict diversity at higher scales? Location: Coastal sand dunes, Aquitaine (France). Methods: Associational patterns with five dominant species were recorded along a local gradient of disturbance and a 240-km long regional gradient. Density, richness, cover and variance ratio of understorey species were recorded in quadrats located in dominant and in open areas. Spatial pattern of dominant plant species was recorded using a distance-based method. Results: Positive understorey-dominant associations were most frequent at both regional and local scale, although negative associations with understorey species were observed for one of the five dominants. At the regional scale, there was a shift in the magnitude of spatial associations, with higher positive associations in the most stressful sites, whereas spatial associations where not affected by the local disturbance gradient. Positive associations were not related to the size of the dominants but rather influenced by the identity of the dominant species. Conclusions: Our study highlights the potential crucial role of facilitation together with the importance of turnover of the dominants in explaining large-scale variation in diversity. However, because positive associations may also be attributed to environmental heterogeneity or co-occurrence of microhabitat preferences of species, experiments are needed to fully assess the relative importance of facilitation versus other drivers of community diversity. [source]

Prediction variance and G-criterion location for split-plot designs

QUALITY AND RELIABILITY ENGINEERING INTERNATIONAL, Issue 4 2009
Wayne R. Wesley
Abstract Prediction variance properties for completely randomized designs (CRD) are fairly well covered in the response surface literature for both spherical and cuboidal designs. This paper evaluates the impact of changes in the variance ratio on the prediction properties of second-order split-plot designs (SPD). It is shown that the variance ratio not only influences the value of the G-criterion but also its location, in contrast with the G-criterion tendencies in CRD. An analytical method, rather than a heuristic optimization algorithm, is used to compute the prediction variance properties, which include the maximum, minimum and integrated variances for second-order SPD. The analytical equations are functions of the design parameters, radius and variance ratio. As a result, the exact values for these quantities are reported along with the location of the maximum prediction variance used in the G-criterion. The two design spaces of the whole plot and the subplot are studied and as a result, relative efficiency values for these distinct spaces are suggested. Copyright © 2008 John Wiley & Sons, Ltd. [source]

Feedback quality adjustment with Bayesian state-space models

APPLIED STOCHASTIC MODELS IN BUSINESS AND INDUSTRY, Issue 2 2007
K. TriantafyllopoulosArticle first published online: 4 DEC 200
Abstract In this paper we develop a Bayesian procedure for feedback adjustment and control of a single process. We replace the usual exponentially weighted moving average (EWMA) predictor by a predictor of a local level model. The novelty of this approach is that the noise variance ratio (NVR) of the local level model is assumed to change stochastically over time. A multiplicative time series model is used to model the evolution of the NVR and a Bayesian algorithm is developed giving the posterior and predictive distributions for both the process and the NVR. The posterior distribution of the NVR allows the modeller to judge better and evaluate the performance of the model. The proposed algorithm is semi-conjugate in the sense that it involves conjugate gamma/beta distributions as well as one step of simulation. The algorithm is fast and is found to outperform the EWMA and other methods. An example considering real data from the microelectronic industry illustrates the proposed methodology. Copyright © 2006 John Wiley & Sons, Ltd. [source]

An empirical analysis of multi-period hedges: Applications to commercial and investment assets

THE JOURNAL OF FUTURES MARKETS, Issue 6 2005
Jimmy E. Hilliard
This study measures the performance of stacked hedge techniques with applications to investment assets and to commercial commodities. The naive stacked hedge is evaluated along with three other versions of the stacked hedge, including those which use exponential and minimum variance ratios. Three commercial commodities (heating oil, light crude oil, and unleaded gasoline) and three investment assets (British Pounds, Deutsche Marks, and Swiss Francs) are examined. The evidence suggests that stacked hedges perform better with investment assets than with commercial commodities. Specifically, deviations from the cost-of-carry model result in nontrivial hedge errors in the stacked hedge. Exponential and minimum variance hedge ratios were found to marginally improve the hedging performance of the stack. © 2005 Wiley Periodicals, Inc. Jrl Fut Mark 25:587,606, 2005 [source]