The estimation of tuberculosis transmission parameters using ABC and MCMC methods
Malyutina, Alina (2014)
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi-fe2014120246768
https://urn.fi/URN:NBN:fi-fe2014120246768
Tiivistelmä
The aim of this work is to apply approximate Bayesian computation in combination
with Marcov chain Monte Carlo methods in order to estimate the parameters of
tuberculosis transmission. The methods are applied to San Francisco data and the
results are compared with the outcomes of previous works. Moreover, a methodological
idea with the aim to reduce computational time is also described. Despite
the fact that this approach is proved to work in an appropriate way, further analysis
is needed to understand and test its behaviour in different cases. Some related
suggestions to its further enhancement are described in the corresponding chapter.
with Marcov chain Monte Carlo methods in order to estimate the parameters of
tuberculosis transmission. The methods are applied to San Francisco data and the
results are compared with the outcomes of previous works. Moreover, a methodological
idea with the aim to reduce computational time is also described. Despite
the fact that this approach is proved to work in an appropriate way, further analysis
is needed to understand and test its behaviour in different cases. Some related
suggestions to its further enhancement are described in the corresponding chapter.