Assessing the short-run effects of lockdown policies on economic activity, with an application to the Santiago Metropolitan Region, Chile

This paper develops a methodology for the assessment of the short-run effects of lockdown policies on economic activity. The methodology combines labor market data with simulation of an agent-based model. We apply our methodology to the Santiago Metropolitan Region, Chile. We recover the model parameters from observed data, taking into account the recurring policy adjustments that characterized the study window. The model is used to build counterfactual scenarios. We estimate an 8 percent output loss in the first 5 months of the pandemic from the policy that was put in place, achieving a 56 percent reduction in the total number of infections. During this period, with an output loss to 10.5 percent of GDP, the infection rate would have decreased 92 percent, significantly delaying the spread of COVID and spike in infections. Our methodology applied to real data provided results that could be valuable in guiding policies in other lockdown situations in times of disaster, pandemics or social upheaval.

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EXPONENTIATED HALF-LOGISTIC LOMAX DISTRIBUTION WITH PROPERTIES AND APPLICATION

NED University Journal of Research ◽

10.35453/nedjr-ascn-2018-0033 ◽

2019 ◽

Vol XVI (2) ◽

pp. 1-11

Author(s):

Farrukh Jamal ◽

Hesham Mohammed Reyad ◽

Soha Othman Ahmed ◽

Muhammad Akbar Ali Shah ◽

Emrah Altun

Keyword(s):

Real Data ◽

Continuous Model ◽

Model Parameters ◽

Data Set ◽

Lomax Distribution ◽

Mathematical Properties ◽

Proposed Model ◽

Probability Weighted Moment ◽

Record Statistics ◽

Maximum Likelihood Criterion

A new three-parameter continuous model called the exponentiated half-logistic Lomax distribution is introduced in this paper. Basic mathematical properties for the proposed model were investigated which include raw and incomplete moments, skewness, kurtosis, generating functions, Rényi entropy, Lorenz, Bonferroni and Zenga curves, probability weighted moment, stress strength model, order statistics, and record statistics. The model parameters were estimated by using the maximum likelihood criterion and the behaviours of these estimates were examined by conducting a simulation study. The applicability of the new model is illustrated by applying it on a real data set.

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Analysis of Cooperative Perception in Ant Traffic and Its Effects on Transportation System by Using a Congestion-Free Ant-Trail Model

Sensors ◽

10.3390/s21072393 ◽

2021 ◽

Vol 21 (7) ◽

pp. 2393

Author(s):

Prafull Kasture ◽

Hidekazu Nishimura

Keyword(s):

Average Velocity ◽

Transportation System ◽

Self Organization ◽

Model Parameters ◽

Agent Based ◽

Model Simulations ◽

Mathematical Representations ◽

Traffic Conditions ◽

Traffic Jams ◽

Ant Trail

We investigated agent-based model simulations that mimic an ant transportation system to analyze the cooperative perception and communication in the system. On a trail, ants use cooperative perception through chemotaxis to maintain a constant average velocity irrespective of their density, thereby avoiding traffic jams. Using model simulations and approximate mathematical representations, we analyzed various aspects of the communication system and their effects on cooperative perception in ant traffic. Based on the analysis, insights about the cooperative perception of ants which facilitate decentralized self-organization is presented. We also present values of communication-parameters in ant traffic, where the system conveys traffic conditions to individual ants, which ants use to self-organize and avoid traffic-jams. The mathematical analysis also verifies our findings and provides a better understanding of various model parameters leading to model improvements.

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Theory and Applications of the Unit Gamma/Gompertz Distribution

Mathematics ◽

10.3390/math9161850 ◽

2021 ◽

Vol 9 (16) ◽

pp. 1850

Author(s):

Rashad A. R. Bantan ◽

Farrukh Jamal ◽

Christophe Chesneau ◽

Mohammed Elgarhy

Keyword(s):

Stochastic Ordering ◽

Real Data ◽

Rate Function ◽

The Other ◽

Likelihood Method ◽

Model Parameters ◽

Data Sets ◽

Gompertz Distribution ◽

Probability And Statistics ◽

Analytical Behavior

Unit distributions are commonly used in probability and statistics to describe useful quantities with values between 0 and 1, such as proportions, probabilities, and percentages. Some unit distributions are defined in a natural analytical manner, and the others are derived through the transformation of an existing distribution defined in a greater domain. In this article, we introduce the unit gamma/Gompertz distribution, founded on the inverse-exponential scheme and the gamma/Gompertz distribution. The gamma/Gompertz distribution is known to be a very flexible three-parameter lifetime distribution, and we aim to transpose this flexibility to the unit interval. First, we check this aspect with the analytical behavior of the primary functions. It is shown that the probability density function can be increasing, decreasing, “increasing-decreasing” and “decreasing-increasing”, with pliant asymmetric properties. On the other hand, the hazard rate function has monotonically increasing, decreasing, or constant shapes. We complete the theoretical part with some propositions on stochastic ordering, moments, quantiles, and the reliability coefficient. Practically, to estimate the model parameters from unit data, the maximum likelihood method is used. We present some simulation results to evaluate this method. Two applications using real data sets, one on trade shares and the other on flood levels, demonstrate the importance of the new model when compared to other unit models.

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Modeling Software Fault-Detection and Fault-Correction Processes by Considering the Dependencies between Fault Amounts

Applied Sciences ◽

10.3390/app11156998 ◽

2021 ◽

Vol 11 (15) ◽

pp. 6998

Author(s):

Qiuying Li ◽

Hoang Pham

Keyword(s):

Time Delay ◽

Fault Detection ◽

Software Reliability ◽

Growth Models ◽

Predictive Performance ◽

Real Data ◽

Reliability Estimation ◽

Model Parameters ◽

Dual Processes ◽

Correction Process

Many NHPP software reliability growth models (SRGMs) have been proposed to assess software reliability during the past 40 years, but most of them have focused on modeling the fault detection process (FDP) in two ways: one is to ignore the fault correction process (FCP), i.e., faults are assumed to be instantaneously removed after the failure caused by the faults is detected. However, in real software development, it is not always reliable as fault removal usually needs time, i.e., the faults causing failures cannot always be removed at once and the detected failures will become more and more difficult to correct as testing progresses. Another way to model the fault correction process is to consider the time delay between the fault detection and fault correction. The time delay has been assumed to be constant and function dependent on time or random variables following some kind of distribution. In this paper, some useful approaches to the modeling of dual fault detection and correction processes are discussed. The dependencies between fault amounts of dual processes are considered instead of fault correction time-delay. A model aiming to integrate fault-detection processes and fault-correction processes, along with the incorporation of a fault introduction rate and testing coverage rate into the software reliability evaluation is proposed. The model parameters are estimated using the Least Squares Estimation (LSE) method. The descriptive and predictive performance of this proposed model and other existing NHPP SRGMs are investigated by using three real data-sets based on four criteria, respectively. The results show that the new model can be significantly effective in yielding better reliability estimation and prediction.

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A New Fuzzy-Based Maximum Power Point Tracker for a Solar Panel Based on Datasheet Values

International Journal of Photoenergy ◽

10.1155/2013/960510 ◽

2013 ◽

Vol 2013 ◽

pp. 1-9 ◽

Cited By ~ 4

Author(s):

Ali Kargarnejad ◽

Mohsen Taherbaneh ◽

Amir Hosein Kashefi

Keyword(s):

Real Data ◽

Point Of View ◽

Solar Panel ◽

Maximum Power ◽

Model Parameters ◽

Maximum Power Point ◽

Knowing That ◽

Stability Point ◽

Power Point ◽

Speed Accuracy

Tracking maximum power point of a solar panel is of interest in most of photovoltaic applications. Solar panel modeling is also very interesting exclusively based on manufacturers data. Knowing that the manufacturers generally give the electrical specifications of their products at one operating condition, there are so many cases in which the specifications in other conditions are of interest. In this research, a comprehensive one-diode model for a solar panel with maximum obtainable accuracy is fully developed only based on datasheet values. The model parameters dependencies on environmental conditions are taken into consideration as much as possible. Comparison between real data and simulations results shows that the proposed model has maximum obtainable accuracy. Then a new fuzzy-based controller to track the maximum power point of the solar panel is also proposed which has better response from speed, accuracy and stability point of view respect to the previous common developed one.

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A new parameter set for anisotropic multiparameter full-waveform inversion and application to a North Sea data set

Geophysics ◽

10.1190/geo2015-0349.1 ◽

2016 ◽

Vol 81 (4) ◽

pp. U25-U38 ◽

Cited By ~ 32

Author(s):

Nuno V. da Silva ◽

Andrew Ratcliffe ◽

Vetle Vinje ◽

Graham Conroy

Keyword(s):

North Sea ◽

Waveform Inversion ◽

Real Data ◽

Model Parameters ◽

Full Waveform Inversion ◽

Radiation Patterns ◽

Data Set ◽

Full Waveform ◽

Seismic Image ◽

Central North Sea

Parameterization lies at the center of anisotropic full-waveform inversion (FWI) with multiparameter updates. This is because FWI aims to update the long and short wavelengths of the perturbations. Thus, it is important that the parameterization accommodates this. Recently, there has been an intensive effort to determine the optimal parameterization, centering the fundamental discussion mainly on the analysis of radiation patterns for each one of these parameterizations, and aiming to determine which is best suited for multiparameter inversion. We have developed a new parameterization in the scope of FWI, based on the concept of kinematically equivalent media, as originally proposed in other areas of seismic data analysis. Our analysis is also based on radiation patterns, as well as the relation between the perturbation of this set of parameters and perturbation in traveltime. The radiation pattern reveals that this parameterization combines some of the characteristics of parameterizations with one velocity and two Thomsen’s parameters and parameterizations using two velocities and one Thomsen’s parameter. The study of perturbation of traveltime with perturbation of model parameters shows that the new parameterization is less ambiguous when relating these quantities in comparison with other more commonly used parameterizations. We have concluded that our new parameterization is well-suited for inverting diving waves, which are of paramount importance to carry out practical FWI successfully. We have demonstrated that the new parameterization produces good inversion results with synthetic and real data examples. In the latter case of the real data example from the Central North Sea, the inverted models show good agreement with the geologic structures, leading to an improvement of the seismic image and flatness of the common image gathers.

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The Gamma Generalized Pareto Distribution with Applications in Survival Analysis

International Journal of Statistics and Probability ◽

10.5539/ijsp.v6n3p141 ◽

2017 ◽

Vol 6 (3) ◽

pp. 141 ◽

Cited By ~ 2

Author(s):

Thiago A. N. De Andrade ◽

Luz Milena Zea Fernandez ◽

Frank Gomes-Silva ◽

Gauss M. Cordeiro

Keyword(s):

Monte Carlo Simulation ◽

Pareto Distribution ◽

Generalized Pareto Distribution ◽

Real Data ◽

Model Parameters ◽

Monte Carlo Simulation Study ◽

Lorenz Curves ◽

Generalized Pareto ◽

Mathematical Properties ◽

Pareto Model

We study a three-parameter model named the gamma generalized Pareto distribution. This distribution extends the generalized Pareto model, which has many applications in areas such as insurance, reliability, finance and many others. We derive some of its characterizations and mathematical properties including explicit expressions for the density and quantile functions, ordinary and incomplete moments, mean deviations, Bonferroni and Lorenz curves, generating function, R\'enyi entropy and order statistics. We discuss the estimation of the model parameters by maximum likelihood. A small Monte Carlo simulation study and two applications to real data are presented. We hope that this distribution may be useful for modeling survival and reliability data.

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A GAMMA MOVING AVERAGE PROCESS FOR MODELLING DEPENDENCE ACROSS DEVELOPMENT YEARS IN RUN-OFF TRIANGLES

Astin Bulletin ◽

10.1017/asb.2020.36 ◽

2020 ◽

pp. 1-22

Author(s):

Luis E. Nieto-Barajas ◽

Rodrigo S. Targino

Keyword(s):

Latent Variables ◽

Moving Average ◽

Real Data ◽

Model Parameters ◽

Average Process ◽

Moving Average Process ◽

Data Set ◽

Run Off ◽

Average Form ◽

Reserve Estimates

ABSTRACT We propose a stochastic model for claims reserving that captures dependence along development years within a single triangle. This dependence is based on a gamma process with a moving average form of order $p \ge 0$ which is achieved through the use of poisson latent variables. We carry out Bayesian inference on model parameters and borrow strength across several triangles, coming from different lines of businesses or companies, through the use of hierarchical priors. We carry out a simulation study as well as a real data analysis. Results show that reserve estimates, for the real data set studied, are more accurate with our gamma dependence model as compared to the benchmark over-dispersed poisson that assumes independence.

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Mixture of Inverse Weibull and Lognormal Distributions: Properties, Estimation, and Illustration

Mathematical Problems in Engineering ◽

10.1155/2015/526786 ◽

2015 ◽

Vol 2015 ◽

pp. 1-8 ◽

Cited By ~ 2

Author(s):

K. S. Sultan ◽

A. S. Al-Moisheer

Keyword(s):

Information Matrix ◽

Real Data ◽

Likelihood Method ◽

Model Parameters ◽

Component Mixture ◽

Data Set ◽

Hazard Functions ◽

Lognormal Distributions ◽

Proposed Model ◽

Estimation Of Model Parameters

We discuss the two-component mixture of the inverse Weibull and lognormal distributions (MIWLND) as a lifetime model. First, we discuss the properties of the proposed model including the reliability and hazard functions. Next, we discuss the estimation of model parameters by using the maximum likelihood method (MLEs). We also derive expressions for the elements of the Fisher information matrix. Next, we demonstrate the usefulness of the proposed model by fitting it to a real data set. Finally, we draw some concluding remarks.

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FULL-WAVEFORM INVERSION WITH SOURCE AND RECEIVER COUPLING EFFECTS CORRECTION

Geophysics ◽

10.1190/geo2020-0331.1 ◽

2021 ◽

pp. 1-37

Author(s):

Xinhai Hu ◽

Wei Guoqi ◽

Jianyong Song ◽

Zhifang Yang ◽

Minghui Lu ◽

...

Keyword(s):

Waveform Inversion ◽

Nonlinear Least Squares ◽

Real Data ◽

Model Parameters ◽

Full Waveform Inversion ◽

Linear Inversion ◽

Near Surface ◽

Model Parameter ◽

Full Waveform ◽

Coupling Factors

Coupling factors of sources and receivers vary dramatically due to the strong heterogeneity of near surface, which are as important as the model parameters for the inversion success. We propose a full waveform inversion (FWI) scheme that corrects for variable coupling factors while updating the model parameter. A linear inversion is embedded into the scheme to estimate the source and receiver factors and compute the amplitude weights according to the acquisition geometry. After the weights are introduced in the objective function, the inversion falls into the category of separable nonlinear least-squares problems. Hence, we could use the variable projection technique widely used in source estimation problem to invert the model parameter without the knowledge of source and receiver factors. The efficacy of the inversion scheme is demonstrated with two synthetic examples and one real data test.

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