v

Computer security : ESORICS 2019 International Workshops, IOSec, MSTEC, and FINSEC, Luxembourg City, Luxembourg, September 26-27, 2019, Revised Selected Papers

European Symposium on Research in Computer Security (24th : 2019 : Luxembourg, Luxembourg)
9783030420512 (electronic bk.)




v

Computational processing of the Portuguese language : 14th International Conference, PROPOR 2020, Evora, Portugal, March 2-4, 2020, Proceedings

PROPOR (Conference) (14th : 2020 : Evora, Portugal)
9783030415051 (electronic bk.)




v

Comprehensive biochemistry for dentistry : textbook for dental students

Gupta, Anil, author.
9789811310355 (electronic bk.)




v

Complete denture prosthodontics : treatment and problem solving

9783319690179 (electronic bk.)




v

Communications and networking : 14th EAI International Conference, ChinaCom 2019, Shanghai, China, November 29 - December 1, 2019, proceedings.

ChinaCom (Conference) (14th : 2019 : Shanghai, China)
9783030411176




v

Common problems in the newborn nursery : an evidence and case-based guide

9783319956725 (electronic bk.)




v

Clinical manual of fever in children

El-Radhi, A. Sahib, author.
9783319923369 (electronic book)




v

Clinical approaches in endodontic regeneration : current and emerging therapeutic perspectives

9783319968483 (electronic bk.)




v

Children’s Palliative Care: An International Case-Based Manual

9783030273750 978-3-030-27375-0




v

Chickpea : crop wild relatives for enhancing genetic gains

9780128183007 (electronic bk.)




v

Cellular internet of things : from massive deployments to critical 5G applications

Liberg, Olof, 1943- author.
9780081029039 (electronic bk.)




v

Brassica improvement : molecular, genetics and genomic perspectives

9783030346942 (electronic bk.)




v

Biomedical product development : bench to bedside

9783030356262 (electronic bk.)




v

Biology and ecology of venomous marine cnidarians

Santhanam, Ramasamy, 1946- author
9789811516030 (electronic bk.)




v

Biological invasions in South Africa

9783030323943 (electronic bk.)




v

Biodiversity of the Himalaya : Jammu and Kashmir State

9789813291744 (electronic bk.)




v

Beyond our genes : pathophysiology of gene and environment interaction and epigenetic inheritance

9783030352134 (electronic bk.)




v

Arctic plants of Svalbard : what we learn from the green in the treeless white world

Lee, Yoo Kyung, author
9783030345600 (electronic bk.)




v

Aquatic biopolymers : understanding their industrial significance and environmental implications

Olatunji, Ololade.
9783030347093 (electronic bk.)




v

Apical periodontitis in root-filled teeth : endodontic retreatment and alternative approaches

9783319572505 (electronic bk.)




v

Anxiety disorders : rethinking and understanding recent discoveries

9789813297050 (electronic bk.)




v

Anomalies of the Developing Dentition : a Clinical Guide to Diagnosis and Management

Soxman, Jane A., author.
9783030031640 (electronic bk.)




v

Animal agriculture : sustainability, challenges and innovations

9780128170526




v

African edible insects as alternative source of food, oil, protein and bioactive components

9783030329525 (electronic bk.)




v

Advances in virus research.

9780123850348 (electronic bk.)




v

Advances in protein chemistry and structural biology.

9780123819635 (electronic bk.)




v

Advances in protein chemistry and structural biology.

9780123864840 (electronic bk.)




v

Advances in parasitology.

9780123742292 (electronic bk.)




v

Advances in cyanobacterial biology

9780128193129 (electronic bk.)




v

Advances in applied microbiology.

1282169459




v

Advances in applied microbiology.

1282169416




v

Advanced age geriatric care : a comprehensive guide

9783319969985 (electronic bk.)




v

A handbook of nuclear applications in humans' lives

Tabbakh, Farshid, author.
9781527544512 (electronic bk.)




v

Notice of Construction - Kennedy Rd. and Ravenshoe Rd.




v

Notice of Construction - Woodbine Ave.




v

COVID-19 Update




v

InBios receives Emergency Use Authorization for its Smart Detect...

InBios International, Inc. announces the U.S. Food and Drug Administration (FDA) issued an emergency use authorization (EUA) for its diagnostic test that can be used immediately by CLIA...

(PRWeb April 08, 2020)

Read the full story at https://www.prweb.com/releases/inbios_receives_emergency_use_authorization_for_its_smart_detect_sars_cov_2_rrt_pcr_kit_for_detection_of_the_virus_causing_covid_19/prweb17036897.htm






v

New Partnerships Emerge for COVID-19 Relief: Dade County Farm Bureau...

Harvested produce crops feed Florida Department of Corrections’ (FDC) more than 87,000 inmates; action saves food costs while reducing COVID-19 related supply chain impacts.

(PRWeb April 20, 2020)

Read the full story at https://www.prweb.com/releases/new_partnerships_emerge_for_covid_19_relief_dade_county_farm_bureau_teams_with_state_leaders_to_launch_farm_to_inmate_program/prweb17052045.htm





v

Jamboree Begins Construction on Capstone Development to Change...

In a public-private partnership to develop housing, resident services and hope for 102 working families in Haster Orangewood community, Jamboree Housing Corporation and the City of Anaheim announce...

(PRWeb April 27, 2020)

Read the full story at https://www.prweb.com/releases/jamboree_begins_construction_on_capstone_development_to_change_trajectory_of_neighborhood_in_anaheim_ca/prweb17073166.htm







v

Penalized generalized empirical likelihood with a diverging number of general estimating equations for censored data

Niansheng Tang, Xiaodong Yan, Xingqiu Zhao.

Source: The Annals of Statistics, Volume 48, Number 1, 607--627.

Abstract:
This article considers simultaneous variable selection and parameter estimation as well as hypothesis testing in censored survival models where a parametric likelihood is not available. For the problem, we utilize certain growing dimensional general estimating equations and propose a penalized generalized empirical likelihood, where the general estimating equations are constructed based on the semiparametric efficiency bound of estimation with given moment conditions. The proposed penalized generalized empirical likelihood estimators enjoy the oracle properties, and the estimator of any fixed dimensional vector of nonzero parameters achieves the semiparametric efficiency bound asymptotically. Furthermore, we show that the penalized generalized empirical likelihood ratio test statistic has an asymptotic central chi-square distribution. The conditions of local and restricted global optimality of weighted penalized generalized empirical likelihood estimators are also discussed. We present a two-layer iterative algorithm for efficient implementation, and investigate its convergence property. The performance of the proposed methods is demonstrated by extensive simulation studies, and a real data example is provided for illustration.




v

Almost sure uniqueness of a global minimum without convexity

Gregory Cox.

Source: The Annals of Statistics, Volume 48, Number 1, 584--606.

Abstract:
This paper establishes the argmin of a random objective function to be unique almost surely. This paper first formulates a general result that proves almost sure uniqueness without convexity of the objective function. The general result is then applied to a variety of applications in statistics. Four applications are discussed, including uniqueness of M-estimators, both classical likelihood and penalized likelihood estimators, and two applications of the argmin theorem, threshold regression and weak identification.




v

Markov equivalence of marginalized local independence graphs

Søren Wengel Mogensen, Niels Richard Hansen.

Source: The Annals of Statistics, Volume 48, Number 1, 539--559.

Abstract:
Symmetric independence relations are often studied using graphical representations. Ancestral graphs or acyclic directed mixed graphs with $m$-separation provide classes of symmetric graphical independence models that are closed under marginalization. Asymmetric independence relations appear naturally for multivariate stochastic processes, for instance, in terms of local independence. However, no class of graphs representing such asymmetric independence relations, which is also closed under marginalization, has been developed. We develop the theory of directed mixed graphs with $mu $-separation and show that this provides a graphical independence model class which is closed under marginalization and which generalizes previously considered graphical representations of local independence. Several graphs may encode the same set of independence relations and this means that in many cases only an equivalence class of graphs can be identified from observational data. For statistical applications, it is therefore pivotal to characterize graphs that induce the same independence relations. Our main result is that for directed mixed graphs with $mu $-separation each equivalence class contains a maximal element which can be constructed from the independence relations alone. Moreover, we introduce the directed mixed equivalence graph as the maximal graph with dashed and solid edges. This graph encodes all information about the edges that is identifiable from the independence relations, and furthermore it can be computed efficiently from the maximal graph.




v

Averages of unlabeled networks: Geometric characterization and asymptotic behavior

Eric D. Kolaczyk, Lizhen Lin, Steven Rosenberg, Jackson Walters, Jie Xu.

Source: The Annals of Statistics, Volume 48, Number 1, 514--538.

Abstract:
It is becoming increasingly common to see large collections of network data objects, that is, data sets in which a network is viewed as a fundamental unit of observation. As a result, there is a pressing need to develop network-based analogues of even many of the most basic tools already standard for scalar and vector data. In this paper, our focus is on averages of unlabeled, undirected networks with edge weights. Specifically, we (i) characterize a certain notion of the space of all such networks, (ii) describe key topological and geometric properties of this space relevant to doing probability and statistics thereupon, and (iii) use these properties to establish the asymptotic behavior of a generalized notion of an empirical mean under sampling from a distribution supported on this space. Our results rely on a combination of tools from geometry, probability theory and statistical shape analysis. In particular, the lack of vertex labeling necessitates working with a quotient space modding out permutations of labels. This results in a nontrivial geometry for the space of unlabeled networks, which in turn is found to have important implications on the types of probabilistic and statistical results that may be obtained and the techniques needed to obtain them.




v

Uniformly valid confidence intervals post-model-selection

François Bachoc, David Preinerstorfer, Lukas Steinberger.

Source: The Annals of Statistics, Volume 48, Number 1, 440--463.

Abstract:
We suggest general methods to construct asymptotically uniformly valid confidence intervals post-model-selection. The constructions are based on principles recently proposed by Berk et al. ( Ann. Statist. 41 (2013) 802–837). In particular, the candidate models used can be misspecified, the target of inference is model-specific, and coverage is guaranteed for any data-driven model selection procedure. After developing a general theory, we apply our methods to practically important situations where the candidate set of models, from which a working model is selected, consists of fixed design homoskedastic or heteroskedastic linear models, or of binary regression models with general link functions. In an extensive simulation study, we find that the proposed confidence intervals perform remarkably well, even when compared to existing methods that are tailored only for specific model selection procedures.