Zobrazeno 1 - 10
of 661
pro vyhledávání: '"Shang, Han"'
Autor:
Shang, Han Lin, Yang, Yang
We propose a nonstationary functional time series forecasting method with an application to age-specific mortality rates observed over the years. The method begins by taking the first-order differencing and estimates its long-run covariance function.
Externí odkaz:
http://arxiv.org/abs/2411.12423
Autor:
Shang, Han Lin
We consider determining change points in a time series of age-specific mortality and fertility curves observed over time. We propose two detection methods for identifying these change points. The first method uses a functional cumulative sum statisti
Externí odkaz:
http://arxiv.org/abs/2411.00534
Fertility differentials by urban-rural residence and nativity of women in Australia significantly impact population composition at sub-national levels. We aim to provide consistent fertility forecasts for Australian women characterized by age, region
Externí odkaz:
http://arxiv.org/abs/2410.18435
This paper introduces a robust estimation strategy for the spatial functional linear regression model using dimension reduction methods, specifically functional principal component analysis (FPCA) and functional partial least squares (FPLS). These te
Externí odkaz:
http://arxiv.org/abs/2410.19140
A function-on-function regression model with quadratic and interaction effects of the covariates provides a more flexible model. Despite several attempts to estimate the model's parameters, almost all existing estimation strategies are non-robust aga
Externí odkaz:
http://arxiv.org/abs/2410.18338
Autor:
Shang, Han Lin, Haberman, Steven
We introduce a compositional power transformation, known as an {\alpha}-transformation, to model and forecast a time series of life-table death counts, possibly with zero counts observed at older ages. As a generalisation of the isometric log-ratio t
Externí odkaz:
http://arxiv.org/abs/2409.11658
Autor:
Shang, Han Lin, Haberman, Steven
Like density functions, period life-table death counts are nonnegative and have a constrained integral, and thus live in a constrained nonlinear space. Implementing established modelling and forecasting methods without obeying these constraints can b
Externí odkaz:
http://arxiv.org/abs/2409.04981
Robust estimation for modern portfolio selection on a large set of assets becomes more important due to large deviation of empirical inference on big data. We propose a distributionally robust methodology for high-dimensional mean-variance portfolio
Externí odkaz:
http://arxiv.org/abs/2405.16989
Time series clustering is an important data mining task with a wide variety of applications. While most methods focus on time series taking values on the real line, very few works consider functional time series. However, functional objects frequentl
Externí odkaz:
http://arxiv.org/abs/2405.04904
We introduce a statistical method for modeling and forecasting functional panel data, where each element is a density. Density functions are nonnegative and have a constrained integral and thus do not constitute a linear vector space. We implement a
Externí odkaz:
http://arxiv.org/abs/2403.13340