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An estimator of winter loss of honey bees in Sweden

Hagö, Elenor (2018) MASK01 20182
Mathematical Statistics
Abstract
The aim of this thesis is to suggest a statistical model to estimate the loss rates of honey bees
during winter in Sweden. The estimator is to be based on annual summary statistics, collected by
the Swedish beekeeping organisation.
Regional specific estimates for winter loss rate is derived by a spatial and temporal hierarchical
model with binomial response. The model is updated by Bayesian inference using Integrated
Nested Laplace Approximations (INLA). Winter loss estimates were derived with probability
intervals and presented on a map of Sweden.
The analysis shows that the average winter loss rates ranges between 10.2 and 19.7 % across the
21 regions, while the differences in average loss rates between years were increasing from... (More)
The aim of this thesis is to suggest a statistical model to estimate the loss rates of honey bees
during winter in Sweden. The estimator is to be based on annual summary statistics, collected by
the Swedish beekeeping organisation.
Regional specific estimates for winter loss rate is derived by a spatial and temporal hierarchical
model with binomial response. The model is updated by Bayesian inference using Integrated
Nested Laplace Approximations (INLA). Winter loss estimates were derived with probability
intervals and presented on a map of Sweden.
The analysis shows that the average winter loss rates ranges between 10.2 and 19.7 % across the
21 regions, while the differences in average loss rates between years were increasing from ranges
9.3 to 18.3 % in 2015, 9.9% to 19.4 % in 2016 and 11.0 to 21.3 % in 2017. Regional differences
were not linked to cultivation zones, when comparing different models with the information
criterions WAIC and DIC.
The analysis included summary statistics from three years. It is possible to expand the model to
include spatial and temporal interaction and trends over time by including summary statistics
from more years. Estimates of winter loss rates based on data from several years have stronger
properties compared to properties due to changes between regions, especially since the
contributing beekeepers may vary a lot from year to year and in each region. (Less)
Please use this url to cite or link to this publication:
author
Hagö, Elenor
supervisor
organization
course
MASK01 20182
year
type
M2 - Bachelor Degree
subject
language
English
id
8959450
date added to LUP
2018-09-26 14:54:58
date last changed
2018-09-26 14:54:58
@misc{8959450,
  abstract     = {The aim of this thesis is to suggest a statistical model to estimate the loss rates of honey bees
during winter in Sweden. The estimator is to be based on annual summary statistics, collected by
the Swedish beekeeping organisation.
Regional specific estimates for winter loss rate is derived by a spatial and temporal hierarchical
model with binomial response. The model is updated by Bayesian inference using Integrated
Nested Laplace Approximations (INLA). Winter loss estimates were derived with probability
intervals and presented on a map of Sweden.
The analysis shows that the average winter loss rates ranges between 10.2 and 19.7 % across the
21 regions, while the differences in average loss rates between years were increasing from ranges
9.3 to 18.3 % in 2015, 9.9% to 19.4 % in 2016 and 11.0 to 21.3 % in 2017. Regional differences
were not linked to cultivation zones, when comparing different models with the information
criterions WAIC and DIC.
The analysis included summary statistics from three years. It is possible to expand the model to
include spatial and temporal interaction and trends over time by including summary statistics
from more years. Estimates of winter loss rates based on data from several years have stronger
properties compared to properties due to changes between regions, especially since the
contributing beekeepers may vary a lot from year to year and in each region.},
  author       = {Hagö, Elenor},
  language     = {eng},
  note         = {Student Paper},
  title        = {An estimator of winter loss of honey bees in Sweden},
  year         = {2018},
}