Latent variable models

Present study aims to examine the relationship between supply chain integration, and IT capability on the supply chain agility in the banking sector of Indonesia, support Maritime and Tourism Business. Moreover, impact of supply chain visibility is examined on supply chain modular design and supply chain agility. The current research aims to analyse the nature of relationships among latent variables; therefore, this study chose the latent analysis technique for investigating these relationships.

12p longtimenosee09 08-04-2024 5 0   Download

The researcher specifies the relation between the latent and observed variables and inter-correlation is allowed between all the factors. This research is based on proposing and evaluating the model based on the association between internal and external collaboration, IT capability, and performance of a firm. The study results in important implications, which are important from managerial and theoretical perspectives.

9p longtimenosee09 08-04-2024 9 0   Download

The widespread adoption of electronic health records allows us to ask evidence-based questions about the need for and benefits of specific clinical interventions in critical-care settings across large populations.

8p visteverogers 24-06-2023 6 2   Download

Structural equation modeling (SEM) is an extremely general and powerful approach to account for measurement error and causal pathways when analyzing data, and it has been used in wide range of applied sciences. There are many commercial and freely available software packages for SEM. However, it is difficult to use any of the packages to analyze general pedigree data, and SEM packages for genetics are limited in their application.

13p vinarcissa 21-03-2023 4 1   Download

(BQ) Ebook Methods in human growth research: Part 2 presents the following content: Parametric models for postnatal growth; parameter estimation in the context of non-linear longitudinal growth models; univariate and bivariate growth references; latent variables and structural equation models; multilevel modeling; methods for the study of the genetics of growth and development; prediction; ordinal longitudinal data analysis.

195p runordie7 30-08-2022 10 3   Download

Single-cell RNA-sequencing (scRNA-seq) allows studying heterogeneity in gene expression in large cell populations. Such heterogeneity can arise due to technical or biological factors, making decomposing sources of variation difficult. We here describe f-scLVM (factorial single-cell latent variable model), a method based on factor analysis that uses pathway annotations to guide the inference of interpretable factors underpinning the heterogeneity.

13p vialfrednobel 29-01-2022 14 0   Download

Accurate discovery of somatic variants is of central importance in cancer research. However, count statistics on discovered somatic insertions and deletions (indels) indicate that large amounts of discoveries are missed because of the quantification of uncertainties related to gap and alignment ambiguities, twilight zone indels, cancer heterogeneity, sample purity, sampling, and strand bias.

25p viarchimedes 26-01-2022 8 0   Download

Culture-independent phylogenetic analysis of 16S ribosomal RNA (rRNA) gene sequences has emerged as an incisive method of profiling bacteria present in a specimen. Currently, multiple techniques are available to enumerate the abundance of bacterial taxa in specimens, including the Sanger sequencing, the ‘next generation’ pyrosequencing, microarrays, quantitative PCR, and the rapidly emerging, third generation sequencing, and fourth generation sequencing methods.

11p viwyoming2711 16-12-2020 14 0   Download

The aim of connectivity mapping is to match drugs using drug-treatment gene expression profiles from multiple cell lines. This can be viewed as an information retrieval task, with the goal of finding the most relevant profiles for a given query drug.

10p vikentucky2711 26-11-2020 12 0   Download

The phenome represents a distinct set of information in the human population. It has been explored particularly in its relationship with the genome to identify correlations for diseases. The phenome has been also explored for drug repositioning with efforts focusing on the search space for the most similar candidate drugs.

12p vikentucky2711 26-11-2020 16 2   Download

Genome-wide association studies (GWASs) have been widely used to discover the genetic basis of complex phenotypes. However, standard single-SNP GWASs suffer from lack of power. In particular, they do not directly account for linkage disequilibrium, that is the dependences between SNPs (Single Nucleotide Polymorphisms).

24p viconnecticut2711 28-10-2020 10 1   Download

Modern developments in single-cell sequencing technologies enable broad insights into cellular state. Single-cell RNA sequencing (scRNA-seq) can be used to explore cell types, states, and developmental trajectories to broaden our understanding of cellular heterogeneity in tissues and organs.

15p vicolorado2711 22-10-2020 15 0   Download

Heterogeneity in the definition and measurement of complex diseases in Genome-Wide Association Studies (GWAS) may lead to misdiagnoses and misclassification errors that can significantly impact discovery of disease loci.

25p vicolorado2711 22-10-2020 6 0   Download

The present paper is concerned with a statistical approach involving latent and manifest variables applied in order to assess the Environmental Management System performance.

11p orianahuynh 10-06-2020 18 2   Download

Communication, behavioural, and executive function problems often co-occur in childhood. Previous attempts to identify the origins of these comorbidities have typically relied on comparisons of different deficit groups and/or latent variable models.

12p virome2711 13-01-2020 15 1   Download

The exchange rate expectations, which are broad models of exchange rate forecasting and efficiency, by looking at approaches, such as the static expectations, the extrapolative, the adaptive, the rational, the regressive, and some general specifications of the above expectations. At the end, orthogonality tests suggest that rejection of the unbiased forward rate hypothesis is caused by different variables (like “news”, unexpected shocks, latent variables, forecast errors in money supplies, interest rate differentials, stock market risk premia, and various forms of conditional variance).

34p trinhthamhodang2 19-01-2020 24 1   Download

Latent conditional models have become popular recently in both natural language processing and vision processing communities. However, establishing an effective and efficient inference method on latent conditional models remains a question. In this paper, we describe the latent-dynamic inference (LDI), which is able to produce the optimal label sequence on latent conditional models by using efficient search strategy and dynamic programming.

9p bunthai_1 06-05-2013 43 1   Download

We propose models for semantic orientations of phrases as well as classification methods based on the models. Although each phrase consists of multiple words, the semantic orientation of the phrase is not a mere sum of the orientations of the component words. Some words can invert the orientation. In order to capture the property of such phrases, we introduce latent variables into the models. Through experiments, we show that the proposed latent variable models work well in the classification of semantic orientations of phrases and achieved nearly 82% classification accuracy. ...

8p bunthai_1 06-05-2013 46 3   Download

Probabilistic Latent Semantic Analysis (PLSA) models have been shown to provide a better model for capturing polysemy and synonymy than Latent Semantic Analysis (LSA). However, the parameters of a PLSA model are trained using the Expectation Maximization (EM) algorithm, and as a result, the trained model is dependent on the initialization values so that performance can be highly variable. In this paper we present a method for using LSA analysis to initialize a PLSA model.

8p bunthai_1 06-05-2013 50 3   Download

We describe two probabilistic models for unsupervised word-sense disambiguation using parallel corpora. The first model, which we call the Sense model, builds on the work of Diab and Resnik (2002) that uses both parallel text and a sense inventory for the target language, and recasts their approach in a probabilistic framework. The second model, which we call the Concept model, is a hierarchical model that uses a concept latent variable to relate different language specific sense labels.

8p bunbo_1 17-04-2013 59 1   Download