10,157 research outputs found
Multivariate Bayesian semiparametric models for authentication of food and beverages
Food and beverage authentication is the process by which foods or beverages
are verified as complying with its label description, for example, verifying if
the denomination of origin of an olive oil bottle is correct or if the variety
of a certain bottle of wine matches its label description. The common way to
deal with an authentication process is to measure a number of attributes on
samples of food and then use these as input for a classification problem. Our
motivation stems from data consisting of measurements of nine chemical
compounds denominated Anthocyanins, obtained from samples of Chilean red wines
of grape varieties Cabernet Sauvignon, Merlot and Carm\'{e}n\`{e}re. We
consider a model-based approach to authentication through a semiparametric
multivariate hierarchical linear mixed model for the mean responses, and
covariance matrices that are specific to the classification categories.
Specifically, we propose a model of the ANOVA-DDP type, which takes advantage
of the fact that the available covariates are discrete in nature. The results
suggest that the model performs well compared to other parametric alternatives.
This is also corroborated by application to simulated data.Comment: Published in at http://dx.doi.org/10.1214/11-AOAS492 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
The implications of inflation in an estimated New-Keynesian model
This paper studies the steady state and dynamic consequences of inflation in an estimated dynamic stochastic general equilibrium model of the U.S. economy. It is found that 10 percentage points of inflation entails a steady state welfare cost as high as 13 percent of annual consumption. This large cost is mainly driven by staggered price contracts and price indexation. The transition from high to low inflation inflicts a welfare loss equivalent to 0.53 percent. The role of nominal/real frictions as well as that of parameter uncertainty is also addressed.Inflation (Finance) ; Econometric models ; Keynesian economics
Do uncertainty and technology drive exchange rates?
This paper investigates the extent to which technology and uncertainty contribute to fluctuations in real exchange rates. Using a structural VAR and bilateral exchange rates, the author finds that neutral technology shocks are important contributors to the dynamics of real exchange rates. Investment-specific and uncertainty shocks have a more restricted effect on international prices. All three disturbances cause short-run deviations from uncovered interest rate parity.Foreign exchange ; Uncertainty ; Technological innovations
Random-set methods identify distinct aspects of the enrichment signal in gene-set analysis
A prespecified set of genes may be enriched, to varying degrees, for genes
that have altered expression levels relative to two or more states of a cell.
Knowing the enrichment of gene sets defined by functional categories, such as
gene ontology (GO) annotations, is valuable for analyzing the biological
signals in microarray expression data. A common approach to measuring
enrichment is by cross-classifying genes according to membership in a
functional category and membership on a selected list of significantly altered
genes. A small Fisher's exact test -value, for example, in this
table is indicative of enrichment. Other category analysis methods retain the
quantitative gene-level scores and measure significance by referring a
category-level statistic to a permutation distribution associated with the
original differential expression problem. We describe a class of random-set
scoring methods that measure distinct components of the enrichment signal. The
class includes Fisher's test based on selected genes and also tests that
average gene-level evidence across the category. Averaging and selection
methods are compared empirically using Affymetrix data on expression in
nasopharyngeal cancer tissue, and theoretically using a location model of
differential expression. We find that each method has a domain of superiority
in the state space of enrichment problems, and that both methods have benefits
in practice. Our analysis also addresses two problems related to
multiple-category inference, namely, that equally enriched categories are not
detected with equal probability if they are of different sizes, and also that
there is dependence among category statistics owing to shared genes. Random-set
enrichment calculations do not require Monte Carlo for implementation. They are
made available in the R package allez.Comment: Published at http://dx.doi.org/10.1214/07-AOAS104 in the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
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