School enrollment among male veterans and nonveterans 20 to 34 years old, October 1983 /

Mode of access: Internet.

1990 census of population and housing. Reference reports.

Mode of access: Internet.

California employment and payrolls in ... /

At head of title: California. Department of Employment affiliated with [U.S.] Social Security Board ...

State Court Caseload Statistics: Annual Report

"SD-C-5"

Earnings replacement from social security and private pensions: newly entitled beneficiaries, 1970.

Mode of access: Internet.

National Defense Program: Contracts and Expenditures

Title varies: June-July 1940, National Defense Program: Contracts and Awards; July 12,1941, National Defense Program: Contract Award Listing

Fishery statistics of the United States /

Mode of access: Internet.

Annual report on transport statistics in the United States.

Issued in parts.

Summary statistics, civil commitment program for narcotic addicts

Mode of access: Internet.

Geology and landslide geomorphology of the Burpee Hills, Skagit County, Washington, USA

Landforms within the Skagit Valley record a complex history of land evolution from Late Pleistocene to the present. Late Pleistocene glacial deposits and subsequent incision by the Skagit River formed the Burpee Hills terrace. The Burpee Hills comprises an approximately 205-m-thick sequence of sediments, including glacio-lacustrine silts and clays, overlain by sandy advance outwash and capped by coarse till, creating a sediment-mantled landscape where mass wasting occurs in the form of debris flows and deep-seated landslides (Heller, 1980; Skagit County, 2014). Landslide probability and location are necessary metrics for informing citizens and policy makers of the frequency of natural hazards. Remote geomorphometric analysis of the site area using airborne LiDAR combined with field investigation provide the information to determine relative ages of landslide deposits, to classify geologic units involved, and to interpret the recent hillslope evolution. Thirty-two percent of the 28-km2 Burpee Hills landform has been mapped as landslide deposits. Eighty-five percent of the south-facing slope is mapped as landslide deposits. The mapped landslides occur predominantly within the advance outwash deposits (Qgav), this glacial unit has a slope angle ranging from 27 to 36 degrees. Quantifying surface roughness as a function of standard deviation of slope provides a relative age of landslide deposits, laying the groundwork for frequency analysis of landslides on the slopes of the Burpee Hills. The south-facing slopes are predominately affected by deep-seated landslides as a result of Skagit River erosion patterns within the floodplain. The slopes eroded at the toe by the Skagit River have the highest roughness coefficients, suggesting that areas with more frequent disturbance at the toe are more prone to sliding or remobilization. Future work including radiocarbon dating and hydrologic-cycle investigations will provide a more accurate timeline of the Burpee Hills hillslope evolution, and better information for emergency management and planners in the future.

Finite mixture regression model with random effects: application to neonatal hospital length of stay

A two-component mixture regression model that allows simultaneously for heterogeneity and dependency among observations is proposed. By specifying random effects explicitly in the linear predictor of the mixture probability and the mixture components, parameter estimation is achieved by maximising the corresponding best linear unbiased prediction type log-likelihood. Approximate residual maximum likelihood estimates are obtained via an EM algorithm in the manner of generalised linear mixed model (GLMM). The method can be extended to a g-component mixture regression model with the component density from the exponential family, leading to the development of the class of finite mixture GLMM. For illustration, the method is applied to analyse neonatal length of stay (LOS). It is shown that identification of pertinent factors that influence hospital LOS can provide important information for health care planning and resource allocation. (C) 2002 Elsevier Science B.V. All rights reserved.

Using mixture models to detect differentially expressed genes

An important and common problem in microarray experiments is the detection of genes that are differentially expressed in a given number of classes. As this problem concerns the selection of significant genes from a large pool of candidate genes, it needs to be carried out within the framework of multiple hypothesis testing. In this paper, we focus on the use of mixture models to handle the multiplicity issue. With this approach, a measure of the local false discovery rate is provided for each gene, and it can be implemented so that the implied global false discovery rate is bounded as with the Benjamini-Hochberg methodology based on tail areas. The latter procedure is too conservative, unless it is modified according to the prior probability that a gene is not differentially expressed. An attractive feature of the mixture model approach is that it provides a framework for the estimation of this probability and its subsequent use in forming a decision rule. The rule can also be formed to take the false negative rate into account.

Subgeometric rates of convergence for a class of continuous-time Markov process

Let (Phi(t))(t is an element of R+) be a Harris ergodic continuous-time Markov process on a general state space, with invariant probability measure pi. We investigate the rates of convergence of the transition function P-t(x, (.)) to pi; specifically, we find conditions under which r(t) vertical bar vertical bar P-t (x, (.)) - pi vertical bar vertical bar -> 0 as t -> infinity, for suitable subgeometric rate functions r(t), where vertical bar vertical bar - vertical bar vertical bar denotes the usual total variation norm for a signed measure. We derive sufficient conditions for the convergence to hold, in terms of the existence of suitable points on which the first hitting time moments are bounded. In particular, for stochastically ordered Markov processes, explicit bounds on subgeometric rates of convergence are obtained. These results are illustrated in several examples.

Uniqueness criteria for continuous-time Markov chains with general transition structures

We derive necessary and sufficient conditions for the existence of bounded or summable solutions to systems of linear equations associated with Markov chains. This substantially extends a famous result of G. E. H. Reuter, which provides a convenient means of checking various uniqueness criteria for birth-death processes. Our result allows chains with much more general transition structures to be accommodated. One application is to give a new proof of an important result of M. F. Chen concerning upwardly skip-free processes. We then use our generalization of Reuter's lemma to prove new results for downwardly skip-free chains, such as the Markov branching process and several of its many generalizations. This permits us to establish uniqueness criteria for several models, including the general birth, death, and catastrophe process, extended branching processes, and asymptotic birth-death processes, the latter being neither upwardly skip-free nor downwardly skip-free.

On the existence of uni-instantaneous Q-processes with a given finite mu-invariant measure

Let S be a countable set and let Q = (q(ij), i, j is an element of S) be a conservative q-matrix over S with a single instantaneous state b. Suppose that we are given a real number mu >= 0 and a strictly positive probability measure m = (m(j), j is an element of S) such that Sigma(i is an element of S) m(i)q(ij) = -mu m(j), j 0 b. We prove that there exists a Q-process P(t) = (p(ij) (t), i, j E S) for which m is a mu-invariant measure, that is Sigma(i is an element of s) m(i)p(ij)(t) = e(-mu t)m(j), j is an element of S. We illustrate our results with reference to the Kolmogorov 'K 1' chain and a birth-death process with catastrophes and instantaneous resurrection.