Page 683 - 8th European Congress of Mathematics ∙ 20-26 June 2021 ∙ Portorož, Slovenia ∙ Book of Abstracts
P. 683
STATISTICS AND FINANCIAL MATHEMATICS
to summarize the time frame of the study, the characteristics of the participants, the outcome
and the time varying covariates, how to summarize longitudinal average trends, how to explore
the variation between individuals, how to characterize the correlation and the covariance of
the outcome and of selected covariates, methods for the exploration of missing values and the
description of drop-out. We provide an example on how to conduct IDA in the context of a lon-
gitudinal population cohort study (Boesch-Supan et al., 2013). The paper is presented on behalf
of the Topic Group “Initial Data Analysis” of the STRATOS Initiative (STRengthening Analyt-
ical Thinking for Observational Studies, http://www.stratos-initiative.org).
References
[1] Huebner, M., le Cessie, S., Schmidt, C.O., Vach, W. A Contemporary Conceptual Frame-
work for Initial Data Analysis. Observational Studies 4 (2018) 171-192.
[2] Boesch-Supan, A., Brandt, M., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., Schaan,
B., Stuck, S., Zuber, S. Data resource profile: the Survey of Health, Ageing and Retirement
in Europe (SHARE), International Journal of Epidemiology 42 (2013) 992—1001.
Recent directions in testing exponentiality: the right-censored data case
Bojana Miloševic´, bojana@matf.bg.ac.rs
University of Belgrade Faculty of Mathematics, Serbia
Coauthor: Marija Cuparic´
Recently the characterizations of distributions have become a very powerful tool for the con-
struction of goodness of fit tests. However, most of such tests have been designed for complete
i.i.d. samples.
Here we introduce the adaptation of several recently proposed classes of characterization
based exponentiality tests for the case of the randomly right-censored data and present their
limiting and small sample properties. The results of a wide empirical study can be used as a
benchmark for future tests proposed for this kind of data. In addition, we present an imputation
procedure that can serve as an alternative approach to adaptation proposal.
Spatial-Temporal Modelling of Temperature for Pricing Temperature
Index Insurance
Che Mohd Imran Che Taib, imran@umt.edu.my
Universiti Malaysia Terengganu, Malaysia
This paper discusses the pricing methodology of the temperature index insurance based on spa-
tial temporal modelling of temperature. The crucial problem here is the location of the potential
insurance buyer relative to the station where index is calculated. Since the observed temper-
atures at particular station are not always correlated to the temperature where the insurance
holder lives, it is important to consider spatial issues in the pricing methodology. Thus, we
model the temperature using spatial temporal stochastic processes and employ the universal
Kriging method to predict the future temperature at some specific locations. Based on tempera-
ture index, we may then price the temperature insurance. We illustrate the pricing methodology
681
to summarize the time frame of the study, the characteristics of the participants, the outcome
and the time varying covariates, how to summarize longitudinal average trends, how to explore
the variation between individuals, how to characterize the correlation and the covariance of
the outcome and of selected covariates, methods for the exploration of missing values and the
description of drop-out. We provide an example on how to conduct IDA in the context of a lon-
gitudinal population cohort study (Boesch-Supan et al., 2013). The paper is presented on behalf
of the Topic Group “Initial Data Analysis” of the STRATOS Initiative (STRengthening Analyt-
ical Thinking for Observational Studies, http://www.stratos-initiative.org).
References
[1] Huebner, M., le Cessie, S., Schmidt, C.O., Vach, W. A Contemporary Conceptual Frame-
work for Initial Data Analysis. Observational Studies 4 (2018) 171-192.
[2] Boesch-Supan, A., Brandt, M., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., Schaan,
B., Stuck, S., Zuber, S. Data resource profile: the Survey of Health, Ageing and Retirement
in Europe (SHARE), International Journal of Epidemiology 42 (2013) 992—1001.
Recent directions in testing exponentiality: the right-censored data case
Bojana Miloševic´, bojana@matf.bg.ac.rs
University of Belgrade Faculty of Mathematics, Serbia
Coauthor: Marija Cuparic´
Recently the characterizations of distributions have become a very powerful tool for the con-
struction of goodness of fit tests. However, most of such tests have been designed for complete
i.i.d. samples.
Here we introduce the adaptation of several recently proposed classes of characterization
based exponentiality tests for the case of the randomly right-censored data and present their
limiting and small sample properties. The results of a wide empirical study can be used as a
benchmark for future tests proposed for this kind of data. In addition, we present an imputation
procedure that can serve as an alternative approach to adaptation proposal.
Spatial-Temporal Modelling of Temperature for Pricing Temperature
Index Insurance
Che Mohd Imran Che Taib, imran@umt.edu.my
Universiti Malaysia Terengganu, Malaysia
This paper discusses the pricing methodology of the temperature index insurance based on spa-
tial temporal modelling of temperature. The crucial problem here is the location of the potential
insurance buyer relative to the station where index is calculated. Since the observed temper-
atures at particular station are not always correlated to the temperature where the insurance
holder lives, it is important to consider spatial issues in the pricing methodology. Thus, we
model the temperature using spatial temporal stochastic processes and employ the universal
Kriging method to predict the future temperature at some specific locations. Based on tempera-
ture index, we may then price the temperature insurance. We illustrate the pricing methodology
681
