The Dynamic Striated Metropolis-Hastings Sampler for High-Dimensional Models

Having efficient and accurate samplers for simulating the posterior distribution is crucial for Bayesian analysis. We develop a generic posterior simulator called the "dynamic striated Metropolis-Hastings (DSMH)" sampler. Grounded in the Metropolis-Hastings algorithm, it draws its strengths from both the equienergy sampler and the sequential Monte Carlo sampler by avoiding the weaknesses of the straight Metropolis-Hastings algorithm as well as those of importance sampling. In particular, the DSMH sampler possesses the capacity to cope with incredibly irregular distributions that are full of winding ridges and multiple peaks and has the flexibility to take full advantage of parallelism on either desktop computers or clusters. The high-dimensional application studied in this paper provides a natural platform to put to the test generic samplers such as the DSMH sampler

"CAN Stop" - Implementation and evaluation of a secondary group prevention for adolescent and young adult cannabis users in various contexts - study protocol

<p>Abstract</p> <p>Background</p> <p>Current research shows that overall numbers for cannabis use among adolescents and young adults dropped in recent years. However, this trend is much less pronounced in continuous cannabis use. With regard to the heightened risk for detrimental health- and development-related outcomes, adolescents and young adults with continuous cannabis use need special attention. The health services structure for adolescents and young adults with substance related problems in Germany, is multifaceted, because different communal, medical and judicial agencies are involved. This results in a rather decentralized organizational structure of the help system. This and further system-inherent characteristics make the threshold for young cannabis users rather high. Because of this, there is a need to establish evidence-based low-threshold help options for young cannabis users, which can be easily disseminated. Therefore, a training programme for young cannabis users (age 14-21) was developed in the "CAN Stop" project. Within the project, we seek to implement and evaluate the training programme within different institutions of the help system. The evaluation is sensitive to the different help systems and their specific prerequisites. Moreover, within this study, we also test the practicability of a training provision through laypersons.</p> <p>Methods/Design</p> <p>The CAN Stop study is a four-armed randomized wait-list controlled trial. The four arms are needed for the different help system settings, in which the CAN Stop training programme is evaluated: (a) the drug addiction aid and youth welfare system, (b) the out-patient medical system, (c) the in-patient medical system and (d) prisons for juvenile offenders. Data are collected at three points, before and after the training or a treatment as usual, and six months after the end of either intervention.</p> <p>Discussion</p> <p>The CAN Stop study is expected to provide an evidence-based programme for young cannabis users seeking to reduce or quit their cannabis use. Moreover, we seek to gain knowledge about the programme's utility within different settings of the German help system for young cannabis users and information about the settings' specific clientele. The study protocol is discussed with regard to potential difficulties within the different settings.</p> <p>Trial registration</p> <p>ISRCTN: <a href="http://www.controlled-trials.com/ISRCTN57036983">ISRCTN57036983</a></p

Does Banque de France control inflation and unemployment?

We re-estimate statistical properties and predictive power of a set of Phillips curves, which are expressed as linear and lagged relationships between the rates of inflation, unemployment, and change in labour force. For France, several relationships were estimated eight years ago. The change rate of labour force was used as a driving force of inflation and unemployment within the Phillips curve framework. The set of nested models starts with a simplistic version without autoregressive terms and one lagged term of explanatory variable. The lag is determined empirically together with all coefficients. The model is estimated using the Boundary Element Method (BEM) with the least squares method applied to the integral solutions of the differential equations. All models include one structural break might be associated with revisions to definitions and measurement procedures in the 1980s and 1990s as well as with the change in monetary policy in 1994-1995. For the GDP deflator, our original model provided a root mean squared forecast error (RMSFE) of 1.0% per year at a four-year horizon for the period between 1971 and 2004. The rate of CPI inflation is predicted with RMSFE=1.5% per year. For the naive (no change) forecast, RMSFE at the same time horizon is 2.95% and 3.3% per year, respectively. Our model outperforms the naive one by a factor of 2 to 3. The relationships for inflation were successfully tested for cointegration. We have formally estimated several vector error correction (VEC) models for two measures of inflation. At a four year horizon, the estimated VECMs provide significant statistical improvements on the results obtained by the BEM: RMSFE=0.8% per year for the GDP deflator and ~1.2% per year for CPI. For a two year horizon, the VECMs improve RMSFEs by a factor of 2, with the smallest RMSFE=0.5% per year for the GDP deflator.Comment: 25 pages, 12 figure

Structural Vector Autoregressions with Smooth Transition in Variances: The Interaction between U.S. Monetary Policy and the Stock Market

In structural vector autoregressive analysis identifying the shocks of interest via heteroskedasticity has become a standard tool. Unfortunately, the approaches currently used for modelling heteroskedasticity all have drawbacks. For instance, assuming known dates for variance changes is often unrealistic while more exible models based on GARCH or Markov switching residuals are difficult to handle from a statistical and computational point of view. Therefore we propose a modelbased on a smooth change in variance that is exible as well as relatively easy to estimate. The model is applied to a five-dimensional system of U.S. variables to explore the interaction between monetary policy and the stock market. It is found that previously used conventional identification schemes in this context are rejected by the data if heteroskedasticity is allowed for. Shocks identified via heteroskedasticity have a different economic interpretation than the shocks identified using conventional methods

Gene expression of NMDA receptor subunits in the cerebellum of elderly patients with schizophrenia

To determine if NMDA receptor alterations are present in the cerebellum in schizophrenia, we measured NMDA receptor binding and gene expression of the NMDA receptor subunits in a post-mortem study of elderly patients with schizophrenia and non-affected subjects. Furthermore, we assessed influence of genetic variation in the candidate gene neuregulin-1 (NRG1) on the expression of the NMDA receptor in an exploratory study. Post-mortem samples from the cerebellar cortex of ten schizophrenic patients were compared with nine normal subjects. We investigated NMDA receptor binding by receptor autoradiography and gene expression of the NMDA receptor subunits NR1, NR2A, NR2B, NR2C and NR2D by in situ hybridization. For the genetic study, we genotyped the NRG1 polymorphism rs35753505 (SNP8NRG221533). Additionally, we treated rats with the antipsychotics haloperidol or clozapine and assessed cerebellar NMDA receptor binding and gene expression of subunits to examine the effects of antipsychotic treatment. Gene expression of the NR2D subunit was increased in the right cerebellum of schizophrenic patients compared to controls. Individuals carrying at least one C allele of rs35753505 (SNP8NRG221533) showed decreased expression of the NR2C subunit in the right cerebellum, compared to individuals homozygous for the T allele. Correlation with medication parameters and the animal model revealed no treatment effects. In conclusion, increased NR2D expression results in a hyperexcitable NMDA receptor suggesting an adaptive effect due to receptor hypofunction. The decreased NR2C expression in NRG1 risk variant may cause a deficit in NMDA receptor function. This supports the hypothesis of an abnormal glutamatergic neurotransmission in the right cerebellum in the pathophysiology of schizophrenia