Análisis de series temporales climáticas
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2020
Defense date
07/2020
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Abstract
El trabajo que se presenta a continuación tiene como objetivo encontrar un modelo que ajuste una serie temporal climática para, en el futuro, poder hacer predicciones, más o menos fiables, sobre el comportamiento del clima. En lo que a metodología se refiere, el trabajo gira en torno a la aplicación de la técnica del bootstrapping para calcular el estimador bootstrap de la desviación típica en una serie de datos dependientes. En términos generales, el bootstrap se utiliza para aproximar la distribución muestral del estimador, extrayendo muestras aleatorias de los datos.
The aim of the work presented below is to find a model that adjusts a climate time series in order to make more or less reliable predictions of climate behaviour in the future. In terms of methodology, the work revolves around the application of the bootstrapping technique to calculate the standard deviation bootstrap estimator on a series of dependent data. In general terms, bootstrapping is used to approximate the estimator's sample distribution by extracting random samples from the data.
The aim of the work presented below is to find a model that adjusts a climate time series in order to make more or less reliable predictions of climate behaviour in the future. In terms of methodology, the work revolves around the application of the bootstrapping technique to calculate the standard deviation bootstrap estimator on a series of dependent data. In general terms, bootstrapping is used to approximate the estimator's sample distribution by extracting random samples from the data.