Workshop
on
Prediction
for marine resources
Date:
Place: Institute of
Statistical Mathematics, Auditorium
| Program |
9:30-10:25
1.
Byeong
U.
Park (Department of
Statistics, Seoul
National University)
Nonparametric
regression techniques: A broad perspective
2. Tsukasa
Hokimoto (
Predictability on
spatiotemporal distribution of chlorophyll in the
Lunch
break................................
3.Kazuhiko
Hiramatsu (National Research Institute of Far Seas
Fisheries)
Development of
fisheries stock management using the operating model
4. Cleridy
Lennert-Cody (Inter-American Tropical Tuna Commission)
An application of
random forests to identify unusual observations in fisheries
data
Tea break
.....................................
5. Masanori
Kawakita (
Shark bycatch
prediction by AdaBoost
6. Mihoko
Minami (Institute of Statistical Mathematics and
Analysis of Shark
bycatch counts by zero-inflated GAM models
| Abstract |
1.
Nonparametric
regression techniques: A broad perspective
In this
presentation, several nonparametric regression techniques are introduced.
Thoseinclude local polynomial fitting, penalized least squares (spline
smoothing), nearest neighbor methods, and wavelet smoothing. Also included are
several techniques of fitting additive regression models, such as marginal
integration, ordinary and smooth backfitting methods. Some extensions to local
quasi-likelihood regression are also discussed.
2. Tsukasa Hokimoto
(
Predictability on
spatiotemporal distribution of chlorophyll in the
In order to predict the change in fish distribution,the prediction of phytoplankton
distribution in the sea has been an important problem. In this talk, we
would like to present the methodology for predicting the change on chlorophyll-a
concentration of the phytoplankton in the Sea of Japan, which is based
on a spatiotemporal statistical model with spatially local structure.
3.Kazuhiko Hiramatsu
(National Research Institute of Far Seas Fisheries)
Development of
fisheries stock management using the operating model
Managing a fisheries
stock is a difficult task. There is
large uncertainty of stock status, biology, and fisheries and conducting
experiments in the marine environment is impossible. Recently management procedures are
investigated using the simulation model (operating model), which represents real
system behavior. The operating model approach allows a laboratory testing of
management procedures and developing the procedure which is robust to
uncertainty. Recent
development of management procedures using the operating model approach is
reviewed in this presentation.
4. Cleridy
Lennert-Cody (Inter-American Tropical Tuna Commission)
An application of
random forests to identify unusual observations in fisheries data
Fisheries observers
of the Inter-American Tropical Tuna Commission collect data on catches and
bycatches aboard purse-seine vessels of the international fishery for tunas in
the eastern
5. Masanori Kawakita
(
Shark bycatch
prediction by AdaBoost
We studied the shark bycatch issue
associated with tuna-fisheries in the eastern
6.
Mihoko Minami
(Institute of Statistical Mathematics and
Analysis of Shark
bycatch counts by zero-inflated GAM models
Shark
bycatch counts are characterized by a large number of zero observations. We
believe that the large proportion of zeros in the data arise because sharks are
not always associated with tunas and they are not caught in such cases. We apply
zero-inflated Poisson regression model and zero-inflated Negative Binomial model
with thin-plate regression splines so that bivariate smooth function of
longitude and latitude can be include in the model.