Fast Filtering and Smoothing for Multivariate State Space Models

This paper gives a new approach to diffuse filtering and smoothing for multivariate state space models. The standard approach treats the observations as vectors while our approach treats each element of the observational vector individually. This strategy leads to computationally efficient methods for multivariate filtering and smoothing. Also, the treatment of the diffuse initial state vector in multivariate models is much simpler than existing methods. The paper presents details of relevant algorithms for filtering, prediction and smoothing. Proofs are provided. Three examples of multivariate models in statistics and economics are presented for which the new approach is particularly relevant.Diffuse initialisation;Kalman filter;multivariate models;smoothing;state space;time series

Adolescent Marijuana Use and Co-Occurrence with Tobacco Use: Implications for Tobacco Regulation

Background: Marijuana use among high school youth has been declining over the past two decades. However, there has been a notable shift in the national landscape with regards to social norms and marijuana legalization that could allow marijuana to become more available and may compete against prevention efforts among youth. Further, youth continue to utilize innovative ways to consume marijuana. There is a documented relationship between marijuana and tobacco use, particularly with the use of blunts. Despite the documented relationship between tobacco and marijuana use, little is known about the modes of marijuana use in relation to different tobacco products. With the recent FDA changes bringing cigars under the purview of the FDA Center for Tobacco Products (CTP), there may be an opportunity for CTP regulations of cigar products to impact youth use of both marijuana and tobacco. Methods: This study used data from the 2015 Cleveland Youth Risk Behavior Survey (n=6197) conducted as a census administration in 26 high schools; overall response rate was 66.5%. Youth were asked “During the past 30 days, how did you usually use marijuana?”. Responses were coded as a blunt; in a joint, bong, or pipe (JBP); or some other way. The standard CDC response categories for this item were altered to allow us to specifically examine blunt use. Analyses were restricted to those who smoked marijuana in the past 30 days and were conducted using SPSSv24. Demographic and tobacco use characteristics were examined for each mode of marijuana use. Result: Overall, 74.6% of past 30-day marijuana users reported usually smoking marijuana as a blunt, 15.1% smoked as a JBP, and 10.4% reported using in some other way. Females were more likely to smoke a blunt (79.5% v 71.1%) and less likely to use some other way (6.7% v 13.1%). Blacks were more likely to smoke a blunt compared to Whites and Hispanics (80.8% v 62.3% and 67.0% respectively); Whites were more likely to smoke a JBP compared to Black and Hispanics (33.8% v. 8.9% and 20.1% respectively). Past 30-day cigarette smokers were more likely to have smoked a JBP and less likely to have smoked a blunt compared to non-cigarette smokers. Conversely, past 30-day cigar smokers were more likely to have smoked a blunt and less likely to have smoked a JBP than non-cigar smokers. Youth who vaped in the past 30-days were more likely to use a JBP and use marijuana in some other way compared to youth who had not vaped. In a multivariable logistic regression predicting blunt use or JBP use, cigar product use increased odds of blunting (OR: 1.98) while hookah use was associated with increased odds of JBP. Conclusion: Cigar products are an easily accessible vehicle for smoking marijuana. Federal regulations to restrict youth access to cigar products could have significant impact on adolescent marijuana use, particularly among females and Black youth

Common business and housing market cycles in the Euro area from a multivariate decomposition.

The 2007 sub-prime crisis in the United States, prolonged by a severe economic recession spread over many countries around the world, has led many economic researchers to focus on the recent fluctuations in housing prices and their relationships with macroeconomics and monetary policies. The existence of common housing cycles among the countries of the euro zone could lead the European Central Bank to integrate more specifically the evolution of such asset prices in its assessment. In this paper, we implement a multivariate unobserved component model on housing market variables in order to assess the common euro area housing cycle and to evaluate its relationship with the economic cycle. Among the general class of multivariate unobserved component models, we implement the band-pass filter based on the trend plus cycle decomposition model and we allow the existence of two cycles of different periods. The dataset consists of gross domestic product and real house prices series for four main euro area countries (Germany, France, Italy and Spain). Empirical results show a strong relationship for business cycles in France, Italy and Spain. Moreover, French and Spanish house prices cycles appear to be strongly related, while the German one possesses its own dynamics. Finally, we find that GDP and house prices cycles are related in the medium-term for fluctuations between 4 and 8 years, while the housing market contributes to the long-term economic growth only in Spain and Germany.House prices, Business cycles, Euro area, Unobserved components model.

An inverse dynamics model for the analysis, reconstruction and prediction of bipedal walking

Walking is a constrained movement which may best be observed during the double stance phase when both feet contact the floor. When analyzing a measured movement with an inverse dynamics model, a violation of these constrains will always occur due to measuring errors and deviations of the segments model from reality, leading to inconsistent results. Consistency is obtained by implementing the constraints into the model. This makes it possible to combine the inverse dynamics model with optimization techniques in order to predict walking patterns or to reconstruct non-measured rotations when only a part of the three-dimensional joint rotations is measured. In this paper the outlines of the extended inverse dynamics method are presented, the constraints which define walking are defined and the optimization procedure is described. The model is applied to analyze a normal walking pattern of which only the hip, knee and ankle flexions/extensions are measured. This input movement is reconstructed to a kinematically and dynamically consistent three-dimensional movement, and the joint forces (including the ground reaction forces) and joint moments of force, needed to bring about this movement are estimated

Ontogenetic and temporal variability in the fat content and fatty acid composition of Atlantic herring (Clupea harengus) from the Bay of Fundy, Canada

Atlantic herring (Clupea harengus) is an ecologically and economically valuable species in many food webs, yet surprisingly little is known about the variation in the nutritional quality of these fish. Atlantic herring collected from 2005 through 2008 from the Bay of Fundy, Canada, were examined for variability in their nutritional quality by using total lipid content (n=889) and fatty acid composition (n=551) as proxies for nutritional value. A significant positive relationship was found between fish length and total lipid content. Atlantic herring also had significantly different fatty acid signatures by age. Fish from 2005 had significantly lower total lipid content than fish from 2006 through 2008, and all years had significantly different fatty acid signatures. Summer fish were significantly fatter than winter fish and had significantly different fatty acid signatures. For all comparisons (ontogenetic, annual, and seasonal) percent concentrations of omega-3, -6, and long-chain monounsaturated fatty acids were the most important for distinguishing between the fatty acid signatures of fish. This study underscores the importance of quantifying variation in prey quality synoptically with prey quantity in food webs over ontogenetic and temporal scales when evaluating the effect of prey nutritional quality on predators and on modeling trophic dynamics

Perceived Job Satisfaction of Nurses Working with Unlicensed Personnel Versus Nurses Working with Licensed Personnel

The purpose of this study was to examine the perceived job satisfaction of nurses who worked primarily with unlicensed assistive personnel (UAP) compared to the job satisfaction of nurses working primarily with licensed personnel. A descriptive comparative study was employed using a random sample of 250 nurses registered in the state of Michigan. Data were collected using a survey methodology. One hundred three nurses responded. Data analysis included a comparison of job satisfaction of participants with the amount of time spent working with unlicensed personnel. The area of practice and level of education of the participants were also compared among those that worked with UAPs. No statistical difference was found when comparing job satisfaction of nurses working primarily with and primarily without UAPs. No statistical difference was found in job satisfaction among the nurses working with UAPs and their area of practice or level of education

A Resupply Scenario For The Columbus Mantended Freeflyer (MTFF)

Within the long-term framework of establishing a coherent system that supports permanent and autonomous European presence in space , the MTFF as an integrated flight configuration assumes a major role among the other COLUMBUS elements and joins Ariane V, HERMES, EDRS and Ground Segment facilities as an important building block, leading to a coherent European space capability. The MTFF is designed for an operational on-orbit period of 30 years, which will be made possible by periodic in-orbit servicing activities. The in-orbit servicing activities are to be made possible by a resupply system, which will have to provide and prepare all items needed for the in-orbit servicing. This will include exchange units for in-orbit maintenance and repair of system and payloads, consumables, new payload sets, etc

Statistical Software for State Space Methods

In this paper we review the state space approach to time series analysis and establish the notation that is adopted in this special volume of the Journal of Statistical Software. We first provide some background on the history of state space methods for the analysis of time series. This is followed by a concise overview of linear Gaussian state space analysis including the modelling framework and appropriate estimation methods. We discuss the important class of unobserved component models which incorporate a trend, a seasonal, a cycle, and fixed explanatory and intervention variables for the univariate and multivariate analysis of time series. We continue the discussion by presenting methods for the computation of different estimates for the unobserved state vector: filtering, prediction, and smoothing. Estimation approaches for the other parameters in the model are also considered. Next, we discuss how the estimation procedures can be used for constructing confidence intervals, detecting outlier observations and structural breaks, and testing model assumptions of residual independence, homoscedasticity, and normality. We then show how ARIMA and ARIMA components models fit in the state space framework to time series analysis. We also provide a basic introduction for non-Gaussian state space models. Finally, we present an overview of the software tools currently available for the analysis of time series with state space methods as they are discussed in the other contributions to this special volume.