ANALISIS HUBUNGAN PRODUKSI PADI DAN INDIKATOR ENSO DI KABUPATEN TABANAN DENGAN PENDEKATAN COPULA
ABSTRACT: Dependence
relationship between two or more variables is an issue that is often studied in
the science of probability and statistics. Pearson correlation is often the
easiest option to measure dependencies between variables. It is well known,
that Pearson correlation assumes that the variable under study must be normally
distributed. However, in reality this is not the case; for example, data in
fields such as climatology and meteorology, insurance, and financial. Copula is
a tool that can be used to model the joint distribution because it does not
require the assumption of normality of the data so that it is resilient against
a wide range of data. In this study, we discussed the application of copula in modeling
the structure of dependencies between two variables: the production of rice and
El-NinoSouthern Oscillation (ENSO) indicator per period in Tabanan Regency. The
best dependency modelstructure is given by the Frank copula of the Archimedean
copula family with estimation parameter, θ = 2,817 and the loglikelihood value
of 3,47.
Penulis: Luh Gede Udayani
Kode Jurnal: jpmatematikadd160167
