William Link, Ph.D. (Former Employee)
Science and Products
Filter Total Items: 44
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Filter Total Items: 122
Estimating migratory game-bird productivity by integrating age ratio and banding data
Context: Reproduction is a critical component of fitness, and understanding factors that influence temporal and spatial dynamics in reproductive output is important for effective management and conservation. Although several indices of reproductive output for wide-ranging species, such as migratory birds, exist, there has been no theoretical justification for their estimators or associated measure
Authors
G.S. Zimmerman, W. A. Link, M.J. Conroy, J.R. Sauer, K.D. Richkus, G. Scott Boomer
Bayesian Inference: with ecological applications
This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational ef
Authors
William A. Link, Richard J. Barker
Spatial patterns of bee captures in North American bowl trapping surveys
1. Bowl and pan traps are now commonly used to capture bees (Hymenoptera: Apiformes) for research and surveys. 2. Studies of how arrangement and spacing of bowl traps affect captures of bees are needed to increase the efficiency of this capture technique. 3. We present results from seven studies of bowl traps placed in trapping webs, grids, and transects in four North American ecoregions (Mid-At
Authors
Sam Droege, Vincent J. Tepedino, Gretchen Lebuhn, William Link, Robert L. Minckley, Qian Chen, Casey Conrad
A Bayesian approach to identifying structural nonlinearity using free-decay response: Application to damage detection in composites
This work discusses a Bayesian approach to approximating the distribution of parameters governing nonlinear structural systems. Specifically, we use a Markov Chain Monte Carlo method for sampling the posterior parameter distributions thus producing both point and interval estimates for parameters. The method is first used to identify both linear and nonlinear parameters in a multiple degree-of-fre
Authors
J.M. Nichols, W. A. Link, K.D. Murphy, C.C. Olson
Bayes factors and multimodel inference
Multimodel inference has two main themes: model selection, and model averaging. Model averaging is a means of making inference conditional on a model set, rather than on a selected model, allowing formal recognition of the uncertainty associated with model choice. The Bayesian paradigm provides a natural framework for model averaging, and provides a context for evaluation of the commonly used AI
Authors
W. A. Link, R. J. Barker
A Bayesian approach to identifying and tracking damage in structures
No abstract available.
Authors
J.M. Nichols, William A. Link, K.D. Murphy, C.C. Olson, F. Bucholtz, J.V. Michalowicz
Postcatastrophe population dynamics and density dependence of an endemic island duck
Laysan ducks (Anas laysanensis) are restricted to approximately 9 km2 in the Northwestern Hawaiian Islands, USA. To evaluate the importance of density dependence for Laysan ducks, we conducted a Bayesian analysis to estimate the parameters of a Gompertz model and the magnitude of process variation and observation error based on the fluctuations in Laysan duck abundance on Laysan Island from 1994 t
Authors
N.E. Seavy, M.H. Reynolds, W. A. Link, J. S. Hatfield
An evaluation of density-dependent and density-independent influences on population growth rates in Weddell seals
Much of the existing literature that evaluates the roles of density-dependent and density-independent factors on population dynamics has been called into question in recent years because measurement errors were not properly dealt with in analyses. Using state-space models to account for measurement errors, we evaluated a set of competing models for a 22-year time series of mark-resight estimates
Authors
J.J. Rotella, W. A. Link, J. D. Nichols, G.L. Hadley, R.A. Garrott, K.M. Proffitt
Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack?Jolly?Seber model
Judicious choice of candidate generating distributions improves efficiency of the Metropolis-Hastings algorithm. In Bayesian applications, it is sometimes possible to identify an approximation to the target posterior distribution; this approximate posterior distribution is a good choice for candidate generation. These observations are applied to analysis of the Cormack?Jolly?Seber model and its
Authors
W. A. Link, R. J. Barker
Combining Breeding Bird Survey and Christmas Bird Count data to evaluate seasonal components of population change in Northern Bobwhite
Annual surveys of wildlife populations provide information about annual rates of change in populations but provide no information about when such changes occur. However, by combining data from 2 annual surveys, conducted in different parts of the year, seasonal components of population change can be estimated. We describe a hierarchical model for simultaneous analysis of 2 continent-scale monitori
Authors
W. A. Link, J.R. Sauer, D.K. Niven
A hierarchical model for estimating change in American Woodcock populations
The Singing-Ground Survey (SGS) is a primary source of information on population change for American woodcock (Scolopax minor). We analyzed the SGS using a hierarchical log-linear model and compared the estimates of change and annual indices of abundance to a route regression analysis of SGS data. We also grouped SGS routes into Bird Conservation Regions (BCRs) and estimated population change and
Authors
J.R. Sauer, W. A. Link, W. L. Kendall, J.R. Kelley, D.K. Niven
Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack-Jolly-Seber model
Judicious choice of candidate generating distributions improves efficiency of the Metropolis-Hastings algorithm. In Bayesian applications, it is sometimes possible to identify an approximation to the target posterior distribution; this approximate posterior distribution is a good choice for candidate generation. These observations are applied to analysis of the Cormack-Jolly-Seber model and its ex
Authors
W. A. Link, R. J. Barker
Science and Products
Filter Total Items: 44
No results found.
Filter Total Items: 122
Estimating migratory game-bird productivity by integrating age ratio and banding data
Context: Reproduction is a critical component of fitness, and understanding factors that influence temporal and spatial dynamics in reproductive output is important for effective management and conservation. Although several indices of reproductive output for wide-ranging species, such as migratory birds, exist, there has been no theoretical justification for their estimators or associated measure
Authors
G.S. Zimmerman, W. A. Link, M.J. Conroy, J.R. Sauer, K.D. Richkus, G. Scott Boomer
Bayesian Inference: with ecological applications
This text provides a mathematically rigorous yet accessible and engaging introduction to Bayesian inference with relevant examples that will be of interest to biologists working in the fields of ecology, wildlife management and environmental studies as well as students in advanced undergraduate statistics.. This text opens the door to Bayesian inference, taking advantage of modern computational ef
Authors
William A. Link, Richard J. Barker
Spatial patterns of bee captures in North American bowl trapping surveys
1. Bowl and pan traps are now commonly used to capture bees (Hymenoptera: Apiformes) for research and surveys. 2. Studies of how arrangement and spacing of bowl traps affect captures of bees are needed to increase the efficiency of this capture technique. 3. We present results from seven studies of bowl traps placed in trapping webs, grids, and transects in four North American ecoregions (Mid-At
Authors
Sam Droege, Vincent J. Tepedino, Gretchen Lebuhn, William Link, Robert L. Minckley, Qian Chen, Casey Conrad
A Bayesian approach to identifying structural nonlinearity using free-decay response: Application to damage detection in composites
This work discusses a Bayesian approach to approximating the distribution of parameters governing nonlinear structural systems. Specifically, we use a Markov Chain Monte Carlo method for sampling the posterior parameter distributions thus producing both point and interval estimates for parameters. The method is first used to identify both linear and nonlinear parameters in a multiple degree-of-fre
Authors
J.M. Nichols, W. A. Link, K.D. Murphy, C.C. Olson
Bayes factors and multimodel inference
Multimodel inference has two main themes: model selection, and model averaging. Model averaging is a means of making inference conditional on a model set, rather than on a selected model, allowing formal recognition of the uncertainty associated with model choice. The Bayesian paradigm provides a natural framework for model averaging, and provides a context for evaluation of the commonly used AI
Authors
W. A. Link, R. J. Barker
A Bayesian approach to identifying and tracking damage in structures
No abstract available.
Authors
J.M. Nichols, William A. Link, K.D. Murphy, C.C. Olson, F. Bucholtz, J.V. Michalowicz
Postcatastrophe population dynamics and density dependence of an endemic island duck
Laysan ducks (Anas laysanensis) are restricted to approximately 9 km2 in the Northwestern Hawaiian Islands, USA. To evaluate the importance of density dependence for Laysan ducks, we conducted a Bayesian analysis to estimate the parameters of a Gompertz model and the magnitude of process variation and observation error based on the fluctuations in Laysan duck abundance on Laysan Island from 1994 t
Authors
N.E. Seavy, M.H. Reynolds, W. A. Link, J. S. Hatfield
An evaluation of density-dependent and density-independent influences on population growth rates in Weddell seals
Much of the existing literature that evaluates the roles of density-dependent and density-independent factors on population dynamics has been called into question in recent years because measurement errors were not properly dealt with in analyses. Using state-space models to account for measurement errors, we evaluated a set of competing models for a 22-year time series of mark-resight estimates
Authors
J.J. Rotella, W. A. Link, J. D. Nichols, G.L. Hadley, R.A. Garrott, K.M. Proffitt
Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack?Jolly?Seber model
Judicious choice of candidate generating distributions improves efficiency of the Metropolis-Hastings algorithm. In Bayesian applications, it is sometimes possible to identify an approximation to the target posterior distribution; this approximate posterior distribution is a good choice for candidate generation. These observations are applied to analysis of the Cormack?Jolly?Seber model and its
Authors
W. A. Link, R. J. Barker
Combining Breeding Bird Survey and Christmas Bird Count data to evaluate seasonal components of population change in Northern Bobwhite
Annual surveys of wildlife populations provide information about annual rates of change in populations but provide no information about when such changes occur. However, by combining data from 2 annual surveys, conducted in different parts of the year, seasonal components of population change can be estimated. We describe a hierarchical model for simultaneous analysis of 2 continent-scale monitori
Authors
W. A. Link, J.R. Sauer, D.K. Niven
A hierarchical model for estimating change in American Woodcock populations
The Singing-Ground Survey (SGS) is a primary source of information on population change for American woodcock (Scolopax minor). We analyzed the SGS using a hierarchical log-linear model and compared the estimates of change and annual indices of abundance to a route regression analysis of SGS data. We also grouped SGS routes into Bird Conservation Regions (BCRs) and estimated population change and
Authors
J.R. Sauer, W. A. Link, W. L. Kendall, J.R. Kelley, D.K. Niven
Efficient implementation of the Metropolis-Hastings algorithm, with application to the Cormack-Jolly-Seber model
Judicious choice of candidate generating distributions improves efficiency of the Metropolis-Hastings algorithm. In Bayesian applications, it is sometimes possible to identify an approximation to the target posterior distribution; this approximate posterior distribution is a good choice for candidate generation. These observations are applied to analysis of the Cormack-Jolly-Seber model and its ex
Authors
W. A. Link, R. J. Barker