Variance reduction

. This strategy is capable to conserve the expected mean of the retailer’s orders while reducing their expected variance. The main contribution here is to reduce the impact of the bullwhip effect on the supplier side by controlling the fulfilled quantities to the retailers. Surprisingly, this proposed strategy eventually improves the service level on the retailer side.

7p longtimenosee10 26-04-2024 5 1   Download

Ebook "Uncertainty in biology: A computational modeling approach" wants to address four main issues related to the building and validation of computational models of biomedical processes: (1) Modeling establishment under uncertainty; (2) Model selection and parameter fitting; (3) Sensitivity analysis and model adaptation; (4) Model predictions under uncertainty in each of the abovementioned areas, the book discusses a number of key-techniques by means of a general theoretical description followed by one or more practical examples.

471p ladongphongthanh1008 22-04-2024 5 2   Download

This paper firstly studies how reliable the SPT data can predict the physical and mechanical properties; secondly, the soil strength is determined in terms of corrected N-SPT values, and finally the bearing capacity of a pile penetrating cohesion soil.

20p nguaconbaynhay11 16-04-2021 17 1   Download

An experiment was conducted to generate a broad genetic variability through induced mutation using physical and chemical mutagens. Three doses each of gamma rays (20, 40 and 60kR), ethyl methane sulphonate (0.2, 0.4 and 0.6%), nitrosoguanidine (0.005, 0.010, and 0.015%), maleic hydrazide (0.01, 0.02 and 0.03%) and their combinations were administered to the seed of two greengram varieties, Sujata and OBGG-52.

13p angicungduoc6 22-07-2020 19 2   Download

This paper investigates the market-risk-hedging effectiveness of the Taiwan Futures Exchange (TAIFEX) stock index futures using daily settlement prices for the period from July 21, 1998 to December 31, 2010. The minimum variance hedge ratios (MVHRs) are estimated from the ordinary least squares regression model (OLS), the vector error correction model (VECM), the generalized autoregressive conditional heteroskedasticity model (GARCH), the threshold GARCH model (TGARCH), and the bivariate GARCH model (BGARCH), respectively.

19p nguyenanhtuan_qb 09-07-2020 21 3   Download

The influence of two factors - "broomrape" and "soil type" on quantities of seven trophic groups of soil microorganisms (Autochthonous; Oligotrophic; Actinomycetes; Microscopic fungi; Ammonifying; Assimilating mineral nitrogen; Aerobic nitrogen-fixing bacteria of the genus Azotobacter) were determined. Soil samples for microbiological analysis were taken from the rhizosphere zone of plants in sunflower crops from two soil types (Haplic Vertisols and Chromic Cambisols), in phenological phases of sunflower and of broomrape - "flowering".

14p nguaconbaynhay6 23-06-2020 11 1   Download

In the present paper, we propose an alternative version of the AMS algorithm, adapted for the first time to the field of particle transport.

10p christabelhuynh 30-05-2020 7 0   Download

In real-world environments, the signals captured by a set of microphones in a speech communication system are mixtures of the desired signal, interference, and ambient noise. A promising solution for proper speech acquisition (with reduced noise and interference) in this context consists in using the linearly constrained minimum variance (LCMV) beamformer to reject the interference, reduce the overall mixture energy, and preserve the target signal.

11p son248 24-03-2020 52 2   Download

The Nigerian economy in the last two decades up until 2013 has been growing at an average of 6% and yet unemployment was equally growing in the region of 20% within the same period. This paradoxical situation has led to a flurry of studies and postulations aimed at providing explanation and solution to the phenomenon. This study making use of a regression model with annual data from 1980 to 2013, empirically determined the impact of public sector expenditures (CEXP and REXP) together with private sector investment (PINV) on unemployment (UNEMP) in Nigeria.

9p chauchaungayxua2 09-01-2020 30 1   Download

An attempt has been made in the present paper to study the agroclimatic potential for the future periods from 2020 to 2099 with A1B-GHG ( Greenhouse Gas Emissions Scenarios) emission scenarios which have been derived from PRECIS (Providing Regional Climate for impact Studies). Rainfall data was used to estimate decadal change in the stable rainfall at various growth stages of transplanted rice of five different representative stations pertaining to Terai, Old Alluvial, New Alluvial, Red & Laterite, and Coastal Saline zones of West Bengal.

10p quenchua2 15-12-2019 10 1   Download

The correlation coefficients may complete information on the relationship between different traits and not to provide benefits according to several multivariate statistical analyses to understand the deep structure of data, factor analysis can be used. Factor analysis techniques used for the main purpose consists of data reduction, summarization of data and represent observed variables using a small number of factors.

8p cothumenhmong1 11-12-2019 7 0   Download

The purpose of this study is the application of VRTs in code EGSnrc to find the optimal parameters for simulation, the head of accelerator and calculation dose distribution using the MC method.

6p queencongchua3 09-09-2019 11 1   Download

This paper develops an original framework that mathematically expresses the coupling of the weight window and source biasing techniques, allowing the authors to explore the impact of inconsistent source sampling on the variance of MC results. A numerical experiment supports this new framework and suggests that certain classes of problems may be relatively insensitive to inconsistent source sampling schemes with moderate levels of splitting and rouletting.

9p minhxaminhyeu4 26-06-2019 12 0   Download

Solving particle transport problems with the Monte Carlo method is simple - just simulate the particle behavior. The devil is in the details, however. This course provides a balanced approach to the theory and practice of Monte Carlo simulation codes, with lectures on transport, random number generation, random sampling, computational geometry, collision physics, tallies, statistics, eigenvalue calculations, variance reduction, and parallel algorithms.

403p tranthanhkhang93 19-04-2017 39 5   Download

This book presents and develops major numerical methods currently used for solving problems arising in quantitative finance. Our presentation splits into two parts. Part I is methodological, and offers a comprehensive toolkit on numerical methods and algorithms. This includes Monte Carlo simulation, numerical schemes for partial differential equations, stochastic optimization in discrete time, copula functions, transform-based methods and quadrature techniques. Part II is practical, and features a number of self-contained cases.

618p thuymonguyen88 07-05-2013 91 28   Download

Second, information should be thought of as better if it reduces the uncertainty surrounding some future cost or benefit. For instance, future liabilities are inherently uncertain. Information that can narrow the variance on estimates of those uncertain liabilities should be considered better information. Reduced variance is particularly valuable when decision-makers are risk-averse, since a reduction in variance alone can lead to different decisions when there is risk aversion.

14p taisaovanchuavo 26-01-2013 49 6   Download

Adaptive and Recursive Monte Carlo Methods This section discusses more advanced techniques of Monte Carlo integration. As examples of the use of these techniques, we include two rather different, fairly sophisticated, multidimensional Monte Carlo codes: vegas [1,2] , and miser [3]. The techniques that we discuss all fall under the general rubric of reduction of variance (§7.6), but are otherwise quite distinct.

13p babyuni 17-08-2010 56 4   Download

Bayesian Estimation Theory: Basic Definitions Bayesian Estimation The Estimate–Maximise Method Cramer–Rao Bound on the Minimum Estimator Variance Design of Mixture Gaussian Models Bayesian Classification Modeling the Space of a Random Process Summary B ayesian estimation is a framework for the formulation of statistical inference problems. In the prediction or estimation of a random process from a related observation signal, the Bayesian philosophy is based on combining the evidence contained in the signal with prior knowledge of the probability distribution of the process.

54p khinhkha 30-07-2010 75 8   Download