Parametric estimation of a boolean segment process with stochastic restoration estimation

We propose a stochastic restoration estimation (SRE) algorithm to estimate the parameters of the length distribution of a boolean segment process. A boolean segment process is a stochastic process obtained by considering the union of independent random segments attached to random points independently scattered on the plane. Each iteration of the SRE algorithm has two steps: first, censored segments are restored; second, based on these restored data, parameter estimations are updated. With a usually straightforward implementation, this algorithm is particularly interesting when censoring effects are difficult to take into account. We illustrate this method in two situations where the parameter of interest is either the mean of the segment length distribution or the variance of its logarithm. Its application to vine shoot length distribution estimation is presented. © 2000 American Statistical Association, Institute of Mathematical Statistics, and Inreiface Foundation of North America.link_to_subscribed_fulltex

Relation flore potentielle-flore réelle de sols agricoles de Côte-d'Or

L'estimation du stock semencier au semis de cultures d'automne et le dénombrement des levées au cours du cycle cultural ont été réalisés dans 35 parcelles agricoles de la plaine de Dijon (Côte-d'Or). La valeur médiane du stock semencier viable est estimée à 2 864 semences par mètre carré, et le taux moyen de levée à 5,54 % du nombre de semences viables. Ce taux de levée varie en fonction des espèces de 0,9 % chez Kickxia spuria à 32,8 % chez Polygonum persicaria. La dynamique des levées est influencée par les conditions climatiques, et un hiver froid et prolongé favorise des levées de printemps au détriment des levées d'automne pour les espèces à germination automnale préférentielle.Relationship between the seedbank and the actual weed flora in agricultural soils in the Côted'Or. The weed seedbank was estimated at the time of autumn crop sowing and the emergence of seedlings was counted during the cultural cycle in 35 fields on the Dijon plain (Côte-d'Or). The median value for the viable seedbank was estimated at 2 864 seeds/m2 and the average rate of emergence at 5.54% of viable seed content. This average rate varies from 0.9% for Kickxia spuria to 32.8% for Polygonum persicaria. The dynamics of seedlings emergence was influenced by the climatic conditions, and cold and prolonged winter favoured the emergence of spring seedlings to the detriment of the autumn seedlings for species with preferential autumn germinating

Relation flore potentielle-flore réelle de sols agricoles de Côte-d'Or

L'estimation du stock semencier au semis de cultures d'automne et le dénombrement des levées au cours du cycle cultural ont été réalisés dans 35 parcelles agricoles de la plaine de Dijon (Côte-d'Or). La valeur médiane du stock semencier viable est estimée à 2 864 semences par mètre carré, et le taux moyen de levée à 5,54 % du nombre de semences viables. Ce taux de levée varie en fonction des espèces de 0,9 % chez Kickxia spuria à 32,8 % chez Polygonum persicaria. La dynamique des levées est influencée par les conditions climatiques, et un hiver froid et prolongé favorise des levées de printemps au détriment des levées d'automne pour les espèces à germination automnale préférentielle.Relationship between the seedbank and the actual weed flora in agricultural soils in the Côted'Or. The weed seedbank was estimated at the time of autumn crop sowing and the emergence of seedlings was counted during the cultural cycle in 35 fields on the Dijon plain (Côte-d'Or). The median value for the viable seedbank was estimated at 2 864 seeds/m2 and the average rate of emergence at 5.54% of viable seed content. This average rate varies from 0.9% for Kickxia spuria to 32.8% for Polygonum persicaria. The dynamics of seedlings emergence was influenced by the climatic conditions, and cold and prolonged winter favoured the emergence of spring seedlings to the detriment of the autumn seedlings for species with preferential autumn germinating

Estimation of the dispersal distances of an aphid-borne virus in a patchy landscape.

Characterising the spatio-temporal dynamics of pathogens in natura is key to ensuring their efficient prevention and control. However, it is notoriously difficult to estimate dispersal parameters at scales that are relevant to real epidemics. Epidemiological surveys can provide informative data, but parameter estimation can be hampered when the timing of the epidemiological events is uncertain, and in the presence of interactions between disease spread, surveillance, and control. Further complications arise from imperfect detection of disease and from the huge number of data on individual hosts arising from landscape-level surveys. Here, we present a Bayesian framework that overcomes these barriers by integrating over associated uncertainties in a model explicitly combining the processes of disease dispersal, surveillance and control. Using a novel computationally efficient approach to account for patch geometry, we demonstrate that disease dispersal distances can be estimated accurately in a patchy (i.e. fragmented) landscape when disease control is ongoing. Applying this model to data for an aphid-borne virus (Plum pox virus) surveyed for 15 years in 605 orchards, we obtain the first estimate of the distribution of flight distances of infectious aphids at the landscape scale. About 50% of aphid flights terminate beyond 90 m, which implies that most infectious aphids leaving a tree land outside the bounds of a 1-ha orchard. Moreover, long-distance flights are not rare-10% of flights exceed 1 km. By their impact on our quantitative understanding of winged aphid dispersal, these results can inform the design of management strategies for plant viruses, which are mainly aphid-borne

Impact of the number of introduction patches (<i>κ</i>) on the expected Fisher information for the sharka epidemic.

<p>For each <i>κ</i>, the estimation with the highest mean posterior log-likelihood was retained. For <i>κ</i><10 no introduction patch combination returned a finite posterior log-likelihood. The empirical approximation of the Fisher information was maximal at <i>κ</i> = 11.</p

Parameter sets for four estimation scenarios.

<p>Parameter sets for four estimation scenarios.</p

Comparison of simulated and estimated dispersal kernels.

<p>From left to right: kernels with the minimum, lower quartile, median, upper quartile and maximum Kullback-Leibler (KL) distances (posterior mean), as estimated (red) under the most exhaustive scheme (Θ₄), based on simulated epidemics with short-, medium- and long-range kernels (from top to bottom; black). Kernels are represented by their marginal cumulative distribution function <i>F</i>^1<i>D</i> (with distance from the source represented on the log₁₀ scale). The mean KL distance is indicated for each estimation.</p

Estimated dispersal kernel for the sharka epidemic.

<p>The posterior marginal cumulative distribution function, <i>F</i>^1<i>D</i>, of the fitted dispersal kernel, obtained for <i>κ</i> = 11 (i.e. the number of introduction patches maximising the Fisher information). The plotted posterior distribution was obtained from 4000 MCMC samples. One line is plotted per sample.</p

Summary statistics for parameters estimated from the survey data.

<p>Summary statistics for parameters estimated from the survey data.</p