#### Filter Results:

- Full text PDF available (60)

#### Publication Year

1990

2017

- This year (1)
- Last 5 years (16)
- Last 10 years (27)

#### Publication Type

#### Co-author

#### Journals and Conferences

Learn More

- Kira S. Makarova, Alexei I. Slesarev, +47 authors Deryck J. Mills
- Proceedings of the National Academy of Sciencesâ€¦
- 2006

Lactic acid-producing bacteria are associated with various plant and animal niches and play a key role in the production of fermented foods and beverages. We report nine genome sequences representing the phylogenetic and functional diversity of these bacteria. The small genomes of lactic acid bacteria encode a broad repertoire of transporters for efficientâ€¦ (More)

Extreme value theory for a class of stochastic volatility models, in which the logarithm of the conditional variance follows a Gaussian linear process, is developed. A result for the asymptotic tail behavior of the transformed stochastic volatility process is established and used to prove that the suitably normalized extremes converge in distribution to theâ€¦ (More)

- F. Jay Breidt
- 1995

We propose a new time series representation of persistence in conditional variance called a long memory stochastic volatility (LMSV) model. The LMSV model is constructed by incorporating an ARFIMA process in a standard stochastic volatility scheme. Strongly consistent estimators of the parameters of the model are obtained by maximizing the spectralâ€¦ (More)

Estimation of finite population totals in the presence of auxiliary information is considered. A class of estimators based on local polynomial regression is proposed. Like generalized regression estimators, these estimators are weighted linear combinations of study variables, in which the weights are calibrated to known control totals, but the assumptionsâ€¦ (More)

Jacquier Polson and Rossi J Business and Economic Statistics have pro posed a hierarchical model and Markov Chain Monte Carlo methodology for parameter estima tion and smoothing in a stochastic volatility model where the logarithm of the conditional vari ance follows an autoregressive process In sampling experiments their estimators perform par ticularlyâ€¦ (More)

Estimation of finite population totals in the presence of auxiliary information is considered. A class of estimators based on penalized spline regression is proposed. These estimators are weighted linear combinations of sample observations, with weights calibrated to known control totals. Further, they allow straightforward extensions to multiple auxiliaryâ€¦ (More)

We propose a new small area estimation approach that combines small area random effects with a smooth, nonparametrically specified trend. By using penalized splines as the representation for the nonparametric trend, it is possible to express the small area estimation problem as a mixed effect regression model. We show how this model can be fitted usingâ€¦ (More)

- Todd R. Klaenhammer, Eric Altermann, +21 authors Roland S. Siezen
- Antonie van Leeuwenhoek
- 2002

This review summarizes a collection of lactic acid bacteria that are now undergoing genomic sequencing and analysis. Summaries are presented on twenty different species, with each overview discussing the organisms fundamental and practical significance, nvironmental habitat, and its role in fermentation, bioprocessing, or probiotics. For those projectsâ€¦ (More)

- Zhongjing Lu, F. Jay Breidt, Henry P. Fleming, Eric Altermann, Todd R. Klaenhammer
- International journal of food microbiology
- 2003

A virulent Lactobacillus plantarum bacteriophage, PhiJL-1, was isolated from a commercial cucumber fermentation. The phage was specific for two related strains of L. plantarum, BI7 and its mutant (deficient in malolactate fermenting ability) MU45, which have been evaluated as starter cultures for controlled cucumber fermentation and as biocontrolâ€¦ (More)

An autoregressive-moving average model in which all roots of the autoregressive polynomial are reciprocals of roots of the moving average polynomial and vice versa is called an all-pass time series model. All-pass models generate uncorrelated (white noise) time series, but these series are not independent in the non-Gaussian case. An approximate likelihoodâ€¦ (More)