Time detection for ovulation in a cycle in presence of polycystic ovary syndrome

Document Type

Conference Article

Publication Title

Springer Proceedings in Mathematics and Statistics

Abstract

We study the body temperature variation in four menstrual phases of an individual in presence of Polycystic Ovary Syndrome (PCOS). From the temperature data recorded, we identify the time of ovulation when the cycles are not regular. We obtain growth curve of body temperature by lowess regression. Proliferation rate ddtlogy(t) of body temperature y= y(t) at time t, attains the lowest value near the time of ovulation. Temperature residuals from the growth curves are seen to follow a correlated Gaussian process. Some convergence results of empirical distribution functions used in this context are also discussed. Detection of ovulation time may help the individual to plan in conceiving a child.

First Page

91

Last Page

104

DOI

10.1007/978-3-319-63886-7_3

Publication Date

1-1-2017

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