Gráfico de controle para monitoramento da razão da demanda e mão de obra em retaguarda de serviços no setor bancário.

O monitoramento da razão Z de duas variáveis através de gráfico de controle tem sido um tema recentemente explorado na literatura. Para analisar mais o assunto, o estudo avalia a eficiência e viabilidade de aplicação dessa ferramenta como suporte na tomada de decisão para gerenciamento de capacidade de mão de obra de retaguarda (doravante mencionado como Backoffice) de serviço de empresa do setor bancário. Tradicionalmente, gráficos de controle tem sido utilizados para monitorar o processo produtivo de manufaturas, mas recentemente tem sido adotado para monitoramento de alguns serviços. Apesar de ainda seguir muitos conceitos pioneiros na manufatura, a atividade do setor de serviços apresenta suas particularidades como, por exemplo, a impossibilidade de gerar estoque. Assim, a necessidade de adequar seus recursos à demanda torna-se essencial, sendo fundamental a gestão de controles e sua urgência para que possa reagir rapidamente em caso de variação de demanda e adequar sua capacidade. Em um cenário de restrição de recursos, planejar é crucial para evitar desperdícios e garantir eficiência. O objetivo deste estudo é apresentar o gráfico de controle como ferramenta para monitorar a razão de duas variáveis aleatórias: a demanda e a mão de obra em Backoffice de serviço em um banco. Nesse trabalho, gráfico de controle de Shewhart tradicional e gráfico de controle de Shewhart com regras suplementares são analisados e os resultados obtidos confirmam a possibilidade de utilização da ferramenta de gráficos de controle para o gerenciamento e adequação de mão de obra para atender a demanda. O monitoramento da razão (demanda/ mão de obra) ajudará o gestor a alocar adequadamente o time (mão de obra) de acordo com a demanda e a capacidade produtiva. Como contribuição, o estudo avalia o comportamento da razão Z = X/Y em situação de alta variabilidade da variável X e baixa variabilidade da variável Y .

On the use of correlated beta random variables with animal population modelling

We give reasons why demographic parameters such as survival and reproduction rates are often modelled well in stochastic population simulation using beta distributions. In practice, it is frequently expected that these parameters will be correlated, for example with survival rates for all age classes tending to be high or low in the same year. We therefore discuss a method for producing correlated beta random variables by transforming correlated normal random variables, and show how it can be applied in practice by means of a simple example. We also note how the same approach can be used to produce correlated uniform triangular, and exponential random variables. (C) 2008 Elsevier B.V. All rights reserved.

Conformal deformation of equilibrium measures in normal random ensembles

We investigate the eigenvalue statistics of ensembles of normal random matrices when their order N tends to infinite. In the model, the eigenvalues have uniform density within a region determined by a simple analytic polynomial curve. We study the conformal deformations of equilibrium measures of normal random ensembles to the real line and give sufficient conditions for it to weakly converge to a Wigner measure.

Sums of a Random Number of Random Variables and their Approximations with ν- Accompanying Infinitely Divisible Laws

* Research supported by NATO GRANT CRG 900 798 and by Humboldt Award for U.S. Scientists.

Efficient random variable generation: ratio of uniforms and polar rejection sampling

Monte Carlo techniques, which require the generation of samples from some target density, are often the only alternative for performing Bayesian inference. Two classic sampling techniques to draw independent samples are the ratio of uniforms (RoU) and rejection sampling (RS). An efficient sampling algorithm is proposed combining the RoU and polar RS (i.e. RS inside a sector of a circle using polar coordinates). Its efficiency is shown in drawing samples from truncated Cauchy and Gaussian random variables, which have many important applications in signal processing and communications. RESUMEN. Método eficiente para generar algunas variables aleatorias de uso común en procesado de señal y comunicaciones (por ejemplo, Gaussianas o Cauchy truncadas) mediante la combinación de dos técnicas: "ratio of uniforms" y "rejection sampling".

The ratio of messenger RNA levels of receptor activator of nuclear factor kappa B ligand to osteoprotegerin correlates with bone remodeling indices in normal human cancellous bone but not in osteoarthritis

skeletal disease. Bone remodeling is initiated by osteoclastic resorption followed by osteoblastic formation of new bone. Receptor activator of nuclear factor KB ligand (RANKL) is a newly described regulator of osteoclast formation and function, the activity of which appears to be a balance between interaction with its receptor RANK and with an antagonist binding protein osteoprotegerin (OPG). Therefore, we have examined the relationship between the expression of RANKL, RANK, and OPG and indices of bone structure and turnover in human cancellous bone from the proximal femur. Bone samples were obtained from individuals with osteoarthritis (OA) at joint replacement surgery and from autopsy controls. Histomorphometric analysis of these samples showed that eroded surface (ES/BS) and osteoid surface (OS/BS) were positively associated in both control (p < 0.001) and OA (p < 0.02), indicating that the processes of bone resorption and bone formation remain coupled in OA, as they are in controls. RANKL, OPG, and RANK messenger RNA, (mRNA) were abundant in human cancellous bone, with significant differences between control and OA individuals. In coplotting the molecular and histomorphometric data, strong associations were found between the ratio of RANKL/OPG mRNA and the indices of bone turnover (RANKL/OPG vs. ES/BS: r = 0.93, p < 0.001; RANKL/OPG vs. OS/BS: r = 0.80, p < 0.001). These relationships were not evident in trabecular bone from severe OA, suggesting that bone turnover may be regulated differently in this disease. We propose that the effective concentration of RANKL is related causally to bone turnover.

Approximations and asymptotic expansions for sums of heavy-tailed random variables

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015

Class of correlated random networks with hidden variables

We study a class of models of correlated random networks in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an a priori specified correlation structure. We also present an extension of the class, to map nonequilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system.

Some Properties of Weighted Distributions for Truncated Random Variables

The present study gave emphasis on characterizing continuous probability distributions and its weighted versions in univariate set up. Therefore a possible work in this direction is to study the properties of weighted distributions for truncated random variables in discrete set up. The problem of extending the measures into higher dimensions as well as its weighted versions is yet to be examined. As the present study focused attention to length-biased models, the problem of studying the properties of weighted models with various other weight functions and their functional relationships is yet to be examined.

Characterizations of Life Distributions Using Conditional Expectations of Doubly (Interval) Truncated Random Variables

In this article, we study reliability measures such as geometric vitality function and conditional Shannon’s measures of uncertainty proposed by Ebrahimi (1996) and Sankaran and Gupta (1999), respectively, for the doubly (interval) truncated random variables. In survival analysis and reliability engineering, these measures play a significant role in studying the various characteristics of a system/component when it fails between two time points. The interrelationships among these uncertainty measures for various distributions are derived and proved characterization theorems arising out of them

Identification of models using failure rate and mean residual life of doubly truncated random variables

In this paper, we study the relationship between the failure rate and the mean residual life of doubly truncated random variables. Accordingly, we develop characterizations for exponential, Pareto 11 and beta distributions. Further, we generalize the identities for fire Pearson and the exponential family of distributions given respectively in Nair and Sankaran (1991) and Consul (1995). Applications of these measures in file context of lengthbiased models are also explored

Asymptotic integral kernel for ensembles of random normal matrices with radial potentials

The method of steepest descent is used to study the integral kernel of a family of normal random matrix ensembles with eigenvalue distribution P-N (z(1), ... , z(N)) = Z(N)(-1)e(-N)Sigma(N)(i=1) V-alpha(z(i)) Pi(1 <= i<j <= N) vertical bar z(i) - z(j)vertical bar(2), where V-alpha(z) = vertical bar z vertical bar(alpha), z epsilon C and alpha epsilon inverted left perpendicular0, infinity inverted right perpendicular. Asymptotic formulas with error estimate on sectors are obtained. A corollary of these expansions is a scaling limit for the n-point function in terms of the integral kernel for the classical Segal-Bargmann space. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.3688293]