A Note on likelihood estimation of missing values in time series

Missing values in time series can be treated as unknown parameters and estimated by maximum likelihood, or as random variables and predicted by the expectation of the unknown values given the data. The difference between these two procedures is illustrated by an example. It is argued that the second procedure is, in general, more relevant for estimating missing values in time series

A Note on likelihood estimation of missing values in time series.

Missing values in time series can be treated as unknown parameters and estimated by maximum likelihood, or as random variables and predicted by the expectation of the unknown values given the data. The difference between these two procedures is illustrated by an example. It is argued that the second procedure is, in general, more relevant for estimating missing values in time series.ARIMA models; Interpolation; Mean Square Error;

Bayesian outliers functions for linear models

This paper introduces two new diagnostic tools: the Bayesian outlier curve (BOC) and the Sequential Bayesian outlier curve (SEBOC). Both are built using the posterior odds for every possible number of outliers in a scale contaminated linear model. It is shown that these functions have a cross-validation interpretation, and can be useful to judge the robustness of the fitted model. The computation of these curves is carried out using ideas from stratified sampling

Discurso de investidura como Doctor Honoris Causa del Prof. C. Tiao

Investido Doctor Honoris Causa en el acto del día de la Universidad del curso 02/0

Examination of ozonesonde data for trends and trend changes incorporating solar and Arctic oscillation signals

One major question that arises with the implementation of the Montreal Protocol and its subsequent conventions is our ability to determine that an ozone “recovery” is in process. Toward this we have utilized a statistical model suggested by Reinsel et al. (2002) that utilizes the idea of a trend and a trend change at a specific time and applied it to 12 ozonesonde stations in the midlatitudes of the Northern Hemisphere. The lower stratosphere, in particular, is of significance as this is where the ozone concentration is a maximum and also where heterogeneous ozone losses have been noted. This statistical methodology suffers, however, from the ambiguities of having to select a specific time for the ozone trend to change and the fact that the Mt Pinatubo volcanic aerosols impacted the ozone amount. Within this paper, we analyze the ozonesonde station data utilizing the above model but examine the statistical stability of the computed results by allowing the point of inflection to change from 1995 through 2000 and also exclude varying amounts of data from the post-Pinatubo period. The results indicate that while the impacts of deleting data and changing the inflection point are nontrivial, the overall results are consistent in that there has been a major change in the ozone trend in the time frame of 1996 and that a reasonable scenario is to utilize a change point in 1996 and exclude 2 years of data after the 1991 Mt. Pinatubo eruption. In addition, we include a term for the Arctic oscillation within the statistical model and demonstrate that it is statistically significant

Rare coding variants in ten genes confer substantial risk for schizophrenia

Rare coding variation has historically provided the most direct connections between gene function and disease pathogenesis. By meta-analysing the whole exomes of 24,248 schizophrenia cases and 97,322 controls, we implicate ultra-rare coding variants (URVs) in 10 genes as conferring substantial risk for schizophrenia (odds ratios of 3-50, PPeer reviewe

Pan-cancer analysis of whole genomes

Cancer is driven by genetic change, and the advent of massively parallel sequencing has enabled systematic documentation of this variation at the whole-genome scale(1-3). Here we report the integrative analysis of 2,658 whole-cancer genomes and their matching normal tissues across 38 tumour types from the Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium of the International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA). We describe the generation of the PCAWG resource, facilitated by international data sharing using compute clouds. On average, cancer genomes contained 4-5 driver mutations when combining coding and non-coding genomic elements; however, in around 5% of cases no drivers were identified, suggesting that cancer driver discovery is not yet complete. Chromothripsis, in which many clustered structural variants arise in a single catastrophic event, is frequently an early event in tumour evolution; in acral melanoma, for example, these events precede most somatic point mutations and affect several cancer-associated genes simultaneously. Cancers with abnormal telomere maintenance often originate from tissues with low replicative activity and show several mechanisms of preventing telomere attrition to critical levels. Common and rare germline variants affect patterns of somatic mutation, including point mutations, structural variants and somatic retrotransposition. A collection of papers from the PCAWG Consortium describes non-coding mutations that drive cancer beyond those in the TERT promoter(4); identifies new signatures of mutational processes that cause base substitutions, small insertions and deletions and structural variation(5,6); analyses timings and patterns of tumour evolution(7); describes the diverse transcriptional consequences of somatic mutation on splicing, expression levels, fusion genes and promoter activity(8,9); and evaluates a range of more-specialized features of cancer genomes(8,10-18).Peer reviewe