Data analysis for distance sampling
The effect of data analysis strategies in density estimation of mountain ungulates using distance sampling
... Our results, however, agree with those obtained by Southwell and Weaver ( 1993 ) regarding the loss of precision in estimates when working with truncated and/or binned data. This work also suggests that DS ...
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Adaptive distance sampling
... theory, analysis and survey ...survey data with an effort factor of less than ...completed sampling in the region, allowing these data to be included in the estimate without biasing the ...
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Distance software: design and analysis of distance sampling surveys for estimating population size
... some data sets, especially for spiked data and for some point transect data ...the data well, for example because the estimated proba- bility of detection falls off more quickly with ...
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Distance software: design and analysis of distance sampling surveys for estimating population size
... collecting data while moving between transects can be ...the distance between sections of survey effort along a transect is roughly equal to the separation between successive parallel transects (Buckland et ...
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A Model-Based Approach for Making Ecological Inference from Distance Sampling Data
... the analysis of distance sampling data. Distance sampling has been widely used to estimate abundance (or density) of animals or plants in a spatially explicit study ...modeling ...
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Mixture models for distance sampling detection functions
... example data sets on specific taxa, we note that there is no limitation to the species or survey setup that mixture model detection functions can be used ...survey data where traditional methods produce ...
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Bayesian methods for hierarchical distance sampling models
... the analysis that con- tained more than 50 detections of coveys: Georgia, Iowa, Illinois, Indiana, Kentucky, Missouri, Mississippi, North Carolina, South Carolina, Tennessee and ...truncation distance of ...
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Survey Designs for Distance Sampling: A Study of Zebra Mussels
... 2.2 Our Data Of the twelve lakes surveyed by the University of Minnesota, only two produced adequate data for analysis. These lakes, Lake Burgan and Lake Sylvia, are both located in central Minnesota ...
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Beyond Reuse Distance Analysis: Dynamic Analysis for Characterization of Data Locality Potential
... additional data structures used by the tool quickly exhaust the memory on our ...trace sampling techniques can be applied to tackle scalability issues of this ...
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Incorporating measurement error and density gradients in distance sampling surveys
... effort data to correct the main survey data for the sectors not ...the analysis of the data might have been partly due to the inconsistencies across these two data ...
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Model selection with overdispersed distance sampling data
... We simulated movements of 10, 12, and 15 animals within 1 km 2 study areas in old growth, regrowing, and recently-logged habitats, respectively. Each animal started with a random initial location and heading, after which ...
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Distance sampling in R
... populations. Distance sampling provides a more efficient solution in such ...Conventional distance sampling assumes the observer is located either at a point or moving along a line and will ...
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Model based distance sampling
... Model-Based Distance Sampling ...Conventional distance sampling adopts a mixed approach, using model-based methods for the detection process, and design-based methods to estimate animal ...
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Distance sampling with camera traps
... methods for estimating the proportion of time active from detection times at CTs with the point 326. transect method described here could yield accurate density estimates for many speci[r] ...
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Statistical efficiency in distance sampling
... Distance sampling is a technique for estimating the abundance of animals or other objects in a region, allowing for imperfect ...tance sampling estimator arising from uncertainty about the unknown ...
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Spatial models for distance sampling data : recent developments and future directions
... 2006). Our aims in creating a spatial model of a biological popu- lation are usually twofold: (i) estimating overall abundance and (ii) investigating the relationship between abundance and environmental covariates. As ...
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Sampling Techniques for Big Data Analysis
... the data integration estimators regarding the bias and standard error of the point estimator and the coverage rate of the 95% confidence interval obtained by the Wald-type ...big data sample, and its ...
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The statistical analysis of complex sampling data
... usefulness, sampling practice has been neglected in the training of statisticians, in the textbooks and treatises, and in the planning and analysis of most experiments and ...12). Sampling forms an ...
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Mixed effect models in distance sampling
... would be necessary to make inference on how these birds make use of this habitat. It is important to avoid false inference due to random variation. Hence, Buckland et al. (2009) recommended that repeat surveys be made on ...
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SAMPLING VARIANCES OF HETEROZYGOSITY AND GENETIC DISTANCE
... On the basis of the formulae €or the sampling variances of heterozygosity and genetic distance, we shall also discuss the number of loci and the number of indi- viduals to be studi[r] ...
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