The Nonparametric Analysis of Point Process Data: The Freezing History of Lake Konstanz

Andrew R. Solow Woods Hole Oceanographic Institution, Woods Hole, Massachusetts

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Abstract

Climate records sometimes have the form of point processes (i.e., observations of the times of occurrence of a specified type of event). A central problem in the analysis of point process data is the estimation of the rate function, defined as the expected number of events occurring in a time interval of unit length. This paper describes some simple nonparametric methods for estimating the rate function and for assessing its statistical significance. The methods are applied to the freezing history of Lake Konstanz.

Abstract

Climate records sometimes have the form of point processes (i.e., observations of the times of occurrence of a specified type of event). A central problem in the analysis of point process data is the estimation of the rate function, defined as the expected number of events occurring in a time interval of unit length. This paper describes some simple nonparametric methods for estimating the rate function and for assessing its statistical significance. The methods are applied to the freezing history of Lake Konstanz.

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