[Top] [Prev] [Next] [References]
Confidence intervals are useful to reveal the variability associated with the parameter estimates and can be used for statistical inference. In some cases, theoretical confidence intervals based on asymptotic assumptions are available. In other cases, approximate confidence intervals can be constructed using bootstrap methods (Efron, 1982; Efron and Tibshirani, 1986).
I use the following procedure to construct 95 percent bootstrap confidence intervals. For each cohort of size N, the individuals are sampled with replacement N times to produce a new cohort. For each cohort, I then estimate the parameters following the same procedures as with the parameter estimates of the original data. This is repeated 10,000 times, and for each iteration, the parameter estimates are retained. For each parameter, the 10,000 estimates are sorted, and the estimates that fall at the 2.5th and the 97.5th percentiles are used to construct a 95 per cent confidence interval.
[Top] [Prev] [Next] [References]
Spatial and Temporal Models of Migrating Juvenile Salmon with Applications.
Home | Columbia R. DART | Status & Trends | Inseason Forecasts | Tools & Models | Research & Publications | Library | Site Map | Search
Please direct questions or comments to:
web@cbr.washington.edu
Columbia Basin Research,
School of Aquatic & Fishery Sciences,
University of Washington