A self-excited threshold autoregressive state-space model for menstrual cycles: forecasting menstruation and identifying within-cycle stages based on basal body temperature
From MaRDI portal
Publication:6625635
DOI10.1002/sim.8096zbMATH Open1545.62382MaRDI QIDQ6625635
Ai Kawamori, Keiichi Fukaya, Masumi Kitazawa, Makio Ishiguro
Publication date: 28 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
periodic phenomenaovulationmenstrual cycle length (MCL)phase identificationsequential Bayesian filtering and prediction
Cites Work
- Unnamed Item
- A Bayesian joint model of menstrual cycle length and fecundity
- A Joint Mixed Effects Dispersion Model for Menstrual Cycle Length and Time-to-Pregnancy
- Bayesian Hierarchical Functional Data Analysis Via Contaminated Informative Priors
- Sequential predictions of menstrual cycle lengths
- Modeling menstrual cycle length using a mixture distribution
- Statistical models for human fecundability
- Non-Gaussian State-Space Modeling of Nonstationary Time Series
- Linear Mixed Models with Heterogeneous within-Cluster Variances
- Modeling Human Fertility in the Presence of Measurement Error
- A Bayesian Change-Point Problem with an Application to the Prediction and Detection of Ovulation in Women
- A joint modeling approach for multivariate survival data with random length
- Heterogeneity in fecundability studies: issues and modelling
- Modelling menstrual cycle length and variability at the approach of menopause by using hierarchical change point models
This page was built for publication: A self-excited threshold autoregressive state-space model for menstrual cycles: forecasting menstruation and identifying within-cycle stages based on basal body temperature