Joint Estimation Using Quadratic Estimating Function

A class of martingale estimating functions is convenient and plays an important role for inference for nonlinear time series models. However, when the information about the first four conditional moments of the observed process becomes available, the quadratic estimating functions are more informative. In this paper, a general framework for joint estimation of conditional mean and variance parameters in time series models using quadratic estimating functions is developed. Superiority of the approach is demonstrated by comparing the information associated with the optimal quadratic estimating function with the information associated with other estimating functions. The method is used to study the optimal quadratic estimating functions of the parameters of autoregressive conditional duration (ACD) models, random coefficient autoregressive (RCA) models, doubly stochastic models and regression models with ARCH errors. Closed-form expressions for the information gain are also discussed in some detail

Track A Basic Science

Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/138319/1/jia218438.pd

A Portable remote medical consultation system for the use of distant rural communities

Remote medical monitoring and consultation has become indispensable in order to enhance the availability of better health-care services to the patients in remote rural areas in the country. This paper proposes an inexpensive, easy to handle Remote Medical Consultation System (RMCS) which supports the healthcare workers to carry out their services through bi-directional video and voice communication between the remote end and doctor’s end as well as automated measuring of medical parameters that can be controlled from both ends. RMCS is consisted of a wearable sensors kit, a centralized hardware platform which connects to the medical sensors and devices and a software platform with database for operating and managing the system. RMCS is capable of remotely measuring patient’s blood pressure, heart rate, body temperature, electrocardiogram (ECG), heart sounds and the system’s platform supports to add-on more medical sensors or devices. The key aspect of the system is that it reduces most of the complexity in operation and facilitates the doctors to monitor and diagnose the patients in real-time. RMCS was essentially developed to eliminate the issues of low quality healthcare services in rural areas and to assist in monitoring immobilized patients