Fitting Mixed Effects Models with Big Data

As technology evolves, big data bring us great opportunities to identify patterns which were infeasible to identify from observations before. At the same time, it also brings challenges to Statisticians in analyzing massive data and transforming them into knowledge. Many existing implementations of traditional statistical methods can not cope with the volume of big data. Our research is motivated by the need to fit Linear Mixed Effect (LME) models to big data.Subsampling and divide and conquer (D\&C) methods have been proposed to analyze the big data. In this thesis, we focus on sampling and D\&C methods for fitting LME models with big data. We start with one-way random effect model in Chapter 2 and consider different subsampling methods such as sampling of subjects, sampling of both subjects and repeated measurements, and D\&C methods to estimate the parameters. Estimation procedures, statistical properties, and simulation results are presented. After comparing the estimators from different methods for one-way random effect model, we consider subsampling of subjects and D\&C method for random intercepts model and general linear mixed effects model in Chapters 3 and 4, respectively. Comparisons for different methods are provided at the end of each chapter. Overall we find that the D\&C method has better performance. Finally, we apply subsampling and D\&C method to investigate the relationship between ultraviolet radiation and blood pressure in Chapter 5

The Linguistic Study of Gong Xunming’s Ceramic Painting Art

Gong Xunming is an artist who devotes to ceramic painting art and sticks to his artistic pursuit. His innovation and exploration in ceramic painting art are forever vigorously progressive. Gong commits all his efforts to seek for artistic innovation and newer, higher objectives, without hesitation and never off the track. He shakes off the bondages of nature and traditions. Everything in his paintings faces the sharp contradiction between reality and imagination. His technique of balancing colors gestates the potential genes for modern and future styles. Gong transforms the natural images into abstract ones, and makes them the language to express surreal forms. The new style of his works represents new artistic language and a new world view

Impact of late spring Siberian snow on summer rainfall in South-Central China

Located in the Yangtze River Valley and surrounded by mountains, South-Central China (SCC) frequently suffered from natural disasters such as torrential precipitation, landslide and debris flow. Here we provide corroborative evidence for a link between the late spring (May) snow water equivalent (SWE) over Siberia and the summer (July–August, abbr. JA) rainfall in SCC. We show that, in May, anomalously low SWE over Siberia is robustly related to a large warming from the surface to the mid-troposphere, and to a stationary Rossby wave train from Siberia eastward toward the North Atlantic. On the one hand, over the North Atlantic there exhibits a tripole pattern response of sea surface temperature anomalies in May. It persists to some extent in JA and in turn triggers a wave train propagating downstream across Eurasia and along the Asian jet, as the so-called Silk Road pattern (SRP). On the other hand, over northern Siberia the drier soil occurs in JA, accompanied by an overlying anomalous anticyclone through the positive feedback. This anomalous anticyclone favors the tropospheric cooling over southern Siberia, and the meridional (northward) displacement of the Asian jet (JMD) due to the change in the meridional temperature gradient. The combination of the SRP and the JMD facilitates less water vapor transport from the tropical oceans and anomalous descending motion over SCC, and thus suppresses the precipitation. These findings indicate that May Siberian SWE can be exploited for seasonal predictability of SCC precipitation.acceptedVersio