NDLI: Modeling juvenile salmon migration using A simple markov chain

Content Provider	Springer Nature Link
Author	Steel, E. Ashley Guttorp, Peter Anderson, James J. Caccia, David C.
Copyright Year	2001
Abstract	We describe movement patterns of hatchery-raised, juvenile, spring chinook salmon, Oncorhynchus tshawytscha, using a two-state Markov chain model. The existence of two states, moving and holding, is suggestedby anecdotalinformation from a large radio telemetry study; yet adequate observations of these small-scale fish behaviors are not available for estimating transition probabilities directly. Instead, we estimate the transition probability matrix from travel times within each of 11 river segments using a method of moments approach. Bootstrapped confidence intervals are presented. Results suggest that fish behavior in the region of the confluence between the Grande Ronde and Snake Rivers includes many transitions between moving and staying while fish behavior in the Snake River is more likely to include long periods of staying.
Starting Page	80
Ending Page	88
Page Count	9
File Format	PDF
ISSN	10857117
Journal	Journal of Agricultural, Biological, and Environmental Statistics
Volume Number	6
Issue Number	1
e-ISSN	15372693
Language	English
Publisher	Springer-Verlag
Publisher Date	2001-01-01
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Inverse Gaussian distribution Method of moments Radio telemetry Statistics for Life Sciences, Medicine, Health Sciences Agriculture Environmental Monitoring/Analysis Biostatistics
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Statistics and Probability Environmental Science Agricultural and Biological Sciences Statistics, Probability and Uncertainty

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Uncertainty Analysis for Computationally Expensive Models with Multiple Outputs

Spatial Regression Modeling for Compositional Data With Many Zeros

Modeling spatial-temporal binary data using Markov random fields

Spatio-temporal modeling of fine particulate matter

Estimation of population size using open capture-recapture models

Bayesian multivariate process modeling for prediction of forest attributes

An Approximate Method for Population Toxicokinetic Analysis With Aggregated Data

Improving Crop Model Inference Through Bayesian Melding With Spatially Varying Parameters

Dating chicks: Calibration and discrimination in a nonlinear multivariate hierarchical growth model

Modeling juvenile salmon migration using A simple markov chain

Similar Documents

Uncertainty Analysis for Computationally Expensive Models with Multiple Outputs

Spatial Regression Modeling for Compositional Data With Many Zeros

Modeling spatial-temporal binary data using Markov random fields

Spatio-temporal modeling of fine particulate matter

Estimation of population size using open capture-recapture models

Bayesian multivariate process modeling for prediction of forest attributes

An Approximate Method for Population Toxicokinetic Analysis With Aggregated Data

Improving Crop Model Inference Through Bayesian Melding With Spatially Varying Parameters

Dating chicks: Calibration and discrimination in a nonlinear multivariate hierarchical growth model

Modeling juvenile salmon migration using A simple markov chain