Search results for "Statistics & Probability"
showing 10 items of 436 documents
Bayesian joint modeling of bivariate longitudinal and competing risks data: An application to study patient-ventilator asynchronies in critical care …
2017
Mechanical ventilation is a common procedure of life support in intensive care. Patient-ventilator asynchronies (PVAs) occur when the timing of the ventilator cycle is not simultaneous with the timing of the patient respiratory cycle. The association between severity markers and the events death or alive discharge has been acknowledged before, however, little is known about the addition of PVAs data to the analyses. We used an index of asynchronies (AI) to measure PVAs and the SOFA (sequential organ failure assessment) score to assess overall severity. To investigate the added value of including the AI, we propose a Bayesian joint model of bivariate longitudinal and competing risks data. Th…
Nonsymmetric conical upper density and $k$-porosity
2017
We study how the Hausdorff measure is distributed in nonsymmetric narrow cones in R n \mathbb {R}^n . As an application, we find an upper bound close to n − k n-k for the Hausdorff dimension of sets with large k k -porosity. With k k -porous sets we mean sets which have holes in k k different directions on every small scale.
Towards a mean body for apparel design
2016
This paper focuses on shape average with applications to the apparel industry. Apparel industry uses a consensus sizing system; its major concern is to fit most of the population into it. Since anthropometric measures do not grow linearly, it is important to find prototypes to accurately represent each size. This is done using random compact mean sets, obtained from a cloud of 3D points given by a scanner and applying to the sample a previous definition of mean set. Additionally, two approaches to define confidence sets are introduced. The methodology is applied to data obtained from a real anthropometric survey. This paper has been partially supported by the following grants: TIN2009-14392…
Combining hashing and enciphering algorithms for epidemiological analysis of gathered data.
2008
Summary Objectives: Compiling individual records coming from different sources is necessary for multi-center studies. Legal aspects can be satisfied by implementing anonymization procedures. When using these procedures with a different key for each study it becomes almost impossible to link records from separate data collections. Methods: The originality of the method relies on the way the combination of hashing and enciphering techniques is performed: like in asymmetric encryption, two keys are used but the private key depends on the patient’s identity. Results: The combination of hashing and enciphering techniques provides a great improvement in the overall security of the proposed scheme…
A “Swedish” actuarial balance for a notional defined contribution pension scheme with disability and minimum pension benefits
2017
This article proposes a “Swedish” type actuarial balance sheet (ABS) for a notional defined contribution (NDC) scheme with disability and minimum pension benefits. The proposed ABS splits the pension system in two parts: the pure NDC part and the redistributive part, which includes the assets and liabilities originating from non-contributory rights. The article contains a numerical example that sheds light on the real applicability of our proposal. The model has practical implications that could be of interest to policy-makers, given that it integrates actuarial and social aspects of public pensions and discloses the real cost of redistribution through minimum pensions.
Does More Context Help? Effects of Context Window and Application Source on Retrieval Performance
2021
We study the effect of contextual information obtained from a user’s digital trace on Web search performance. Contextual information is modeled using Dirichlet–Hawkes processes (DHP) and used in augmenting Web search queries. The context is captured by monitoring all naturally occurring user behavior using continuous 24/7 recordings of the screen and associating the context with the queries issued by the users. We report a field study in which 13 participants installed a screen recording and digital activity monitoring system on their laptops for 14 days, resulting in data on all Web search queries and the associated context data. A query augmentation (QAug) model was built to expand the or…
Dynamic network identification from non-stationary vector autoregressive time series
2018
Learning the dynamics of complex systems features a large number of applications in data science. Graph-based modeling and inference underpins the most prominent family of approaches to learn complex dynamics due to their ability to capture the intrinsic sparsity of direct interactions in such systems. They also provide the user with interpretable graphs that unveil behavioral patterns and changes. To cope with the time-varying nature of interactions, this paper develops an estimation criterion and a solver to learn the parameters of a time-varying vector autoregressive model supported on a network of time series. The notion of local breakpoint is proposed to accommodate changes at individu…
Modeling joint and marginal distributions in the analysis of categorical panel data
2001
This article presents a unifying approach to the analysis of repeated univariate categorical (ordered) responses based on the application of the generalized log-linear modeling framework proposed by Lang and Agresti. It is shown that three important research questions in longitudinal studies can be addressed simultaneously. These questions are the following: What is the overall dependence structure of the repeated responses? What is the structure of the change between consecutive time points? and What is the structure of the change in the marginal distributions? Each of these questions involves specifying log-linear models for different marginal distributions of the multiway cross classifi…
Interindividual Differences in Treatment Effects based on Structural Equation Models with Latent Variables: An EffectLiteR Tutorial
2019
The investigation of interindividual differences in the effects of a treatment is challenging, because many constructs-of-interest in psychological research such as depression or anxiety are latent variables and modeling heterogeneity in treatment effects requires interactions and potentially nonlinear relationships. In this paper, we present a tutorial of the EffectLiteR approach (Mayer, Dietzfelbinger, Rosseel, & Steyer, 2016) that allows for estimating individual treatment effects based on latent variable models. We describe step by step how to apply the approach using the EffectLiteR software package with data from the multicenter randomized controlled trial of the Social Phobia…
Encuestas a pie de urna en España. ¿Error muestral o sesgo de no respuesta?
2016
Countless examples of misleading forecasts on behalf of both pre-election and exit polls can be found all over the world. Non-representative samples due to differential nonresponse have been claimed as being the main reason for inaccurate exit-poll projections. In real inference problems, it is seldom possible to compare estimates and true values. Electoral forecasts are an exception. Comparisons between estimates and final outcomes can be carried out once votes have been tallied. In this paper, we examine the raw data collected in seven exit polls conducted in Spain and test the likelihood that the data collected in each sampled voting location can be considered as a random sample of actua…