Metric for Disassembly and Reuse Decisions: Formulation and Validation

2008 ◽  
Author(s):  
Vijitashwa Pandey ◽  
Deborah Thurston
Keyword(s):  
Maximum Likelihood ◽  
Value Function ◽  
Choice Theory ◽  
Decision Makers ◽  
Maximum Likelihood Estimates ◽  
Likelihood Method ◽  
Maximum Value ◽  
Long Range Planning ◽  
The Relationship ◽  
The Value Function

Design for disassembly and reuse focuses on developing methods to minimize difficulty in disassembly for maintenance or reuse. These methods can gain substantially if the relationship between component attributes (material mix, ease of disassembly etc.) and their likelihood of reuse or disposal is understood. For products already in the marketplace, a feedback approach that evaluates willingness of manufacturers or customers (decision makers) to reuse a component can reveal how attributes of a component affect reuse decisions. This paper introduces some metrics and combines them with ones proposed in literature into a measure that captures the overall value of a decision made by the decision makers. The premise is that the decision makers would choose a decision that has the maximum value. Four decisions are considered regarding a component’s fate after recovery ranging from direct reuse to disposal. A method on the lines of discrete choice theory is utilized that uses maximum likelihood estimates to determine the parameters that define the value function. The maximum likelihood method can take inputs from actual decisions made by the decision makers to assess the value function. This function can be used to determine the likelihood that the component takes a certain path (one of the four decisions), taking as input its attributes, which can facilitate long range planning and also help determine ways reuse decisions can be influenced.

scholarly journals Robust parametric estimates of inhomogeneous experimental data

2020 ◽  
pp. 55-62
Author(s):  
V.A. Simakhin ◽  
◽  
L.G. Shamanaeva ◽  
A.E. Avdyushina ◽  
◽  
...  
Keyword(s):  
Experimental Data ◽  
Maximum Likelihood ◽  
Maximum Likelihood Method ◽  
Maximum Likelihood Estimates ◽  
Likelihood Method ◽  
Robust Estimates

In the present work, a weighed maximum likelihood method (WMLM) is proposed to obtain robust estimates for processing experimental data containing outliers. The method allows robust asymptotic unbiased and effective estimates to be obtained in the presence of not only external, but also internal asymmetric and symmetric outliers. Algorithms for obtaining robust WMLM estimates are considered at the parametric level of aprioristic uncertainty. It is demonstrated that these estimates converge to maximum likelihood estimates of an inhomogeneous sample for each distribution from the Tukey supermodel.

scholarly journals On Modified Burr XII-Inverse Weibull Distribution: Development, Properties, Characterizations and Applications

2020 ◽  
pp. 721-735
Author(s):  
Fiaz Ahmad Bhatti ◽  
G. G. Hamedani ◽  
Haitham M. Yousof ◽  
Azeem Ali ◽  
Munir Ahmad
Keyword(s):  
Maximum Likelihood ◽  
Hazard Rate ◽  
Maximum Likelihood Method ◽  
Real Data ◽  
Lifetime Distribution ◽  
Maximum Likelihood Estimates ◽  
Likelihood Method ◽  
Data Sets ◽  
Quarterly Earnings ◽  
Inverse Weibull Distribution

A flexible lifetime distribution with increasing, decreasing, inverted bathtub and modified bathtub hazard rate called Modified Burr XII-Inverse Weibull (MBXII-IW) is introduced and studied. The density function of MBXII-IW is exponential, left-skewed, right-skewed and symmetrical shaped.  Descriptive measures on the basis of quantiles, moments, order statistics and reliability measures are theoretically established. The MBXII-IW distribution is characterized via different techniques. Parameters of MBXII-IW distribution are estimated using maximum likelihood method. The simulation study is performed to illustrate the performance of the maximum likelihood estimates (MLEs). The potentiality of MBXII-IW distribution is demonstrated by its application to real data sets: serum-reversal times and quarterly earnings.

An application of Bayesian techniques to the genetic evaluation of growth traits in Eucalyptus globulus

1998 ◽  
Vol 28 (9) ◽  
pp. 1286-1294 ◽  
Author(s):  
F Soria ◽  
F Basurco ◽  
G Toval ◽  
L Silió ◽  
M C Rodriguez ◽  
...  
Keyword(s):  
Maximum Likelihood ◽  
Eucalyptus Globulus ◽  
Maximum Likelihood Estimates ◽  
Breeding Value ◽  
Likelihood Method ◽  
Phenotypic Correlation ◽  
Data Set ◽  
Breeding Values ◽  
Bayesian Techniques ◽  
Self Pollination

A Bayesian procedure coupled with Gibbs sampling was implemented to obtain inferences about genetic parameters and breeding values for height and diameter of 7-year-old Eucalyptus globulus Labill. is described. The data set consisted of 21 708 trees from 260 open-pollinated families taken from 10 different Australian provenances, from one Spanish population, and from two clones. The trees are distributed over eight sites in the south of Spain, with 20 blocks per site. Data were corrected for heterogeneity of phenotypic variances between blocks. In the analysis, a self-pollination rate of 30% for the open-pollinated families is assumed in the relationship matrix. The posterior means (and standard deviations) of the heritabilities of height and diameter and the genetic and phenotypic correlation were 0.217 (0.014), 0.128 (0.084), 0.768 (0.028), and 0.799 (0.003). Results from the standard restricted maximum likelihood method were 0.173, 0.113, 0.759, and 0.798, respectively. Most of the discrepancy in heritability estimates from both methods can be attributed to the adjustement of residual maximum likelihood estimates to the assumed self-pollination rate, which ignores the presence of clones in the trial. The effect of the method of prediction of breeding values (best linear unbiased prediction or Bayesian techniques) on the genetic superiority of the selected trees was not important. Differences in breeding value among provenances and among families were evidenced for both traits.

The Estimated Probability of Dizygotic Twins: A Comparison of Two Methods

2009 ◽  
Vol 12 (1) ◽  
pp. 79-85 ◽  
Author(s):  
Jill Hardin ◽  
Steve Selvin ◽  
Suzan L. Carmichael ◽  
Gary M. Shaw
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Estimation ◽  
Likelihood Estimation ◽  
Data Sources ◽  
Maximum Likelihood Estimates ◽  
Estimation Methods ◽  
Dizygotic Twin ◽  
Twin Data ◽  
Dizygotic Twins ◽  
The Relationship

AbstractThis study presents a general model of two binary variables and applies it to twin sex pairing data from 21 twin data sources to estimate the frequency of dizygotic twins. The purpose of this study is to clarify the relationship between maximum likelihood and Weinberg's differential rule zygosity estimation methods. We explore the accuracy of these zygosity estimation measures in relation to twin ascertainment methods and the probability of a male. Twin sex pairing data from 21 twin data sources representing 15 countries was collected for use in this study. Maximum likelihood estimation of the probability of dizygotic twins is applied to describe the variation in the frequency of dizygotic twin births. The differences between maximum likelihood and Weinberg's differential rule zygosity estimation methods are presented as a function of twin data ascertainment method and the probability of a male. Maximum likelihood estimation of the probability of dizygotic twins ranges from 0.083 (95% approximate CI: 0.082, 0.085) to 0.750 (95% approximate CI: 0.749, 0.752) for voluntary ascertainment data sources and from 0.374 (95% approximate CI: 0.373, 0.375) to 0.987 (95% approximate CI: 0.959, 1.016) for active ascertainment data sources. In 17 of the 21 twin data sources differences of 0.01 or less occur between maximum likelihood and Weinberg zygosity estimation methods. The Weinberg and maximum likelihood estimates are negligibly different in most applications. Using the above general maximum likelihood estimate, the probability of a dizygotic twin is subject to substantial variation that is largely a function of twin data ascertainment method.

The Relationship Between Numeracy and the Value Function and Probability Weighting in Prospect Theory

2012 ◽  
Author(s):  
Mona Gauth ◽  
Maria Henriksson ◽  
Peter Juslin ◽  
Neda Kerimi ◽  
Marcus Lindskog ◽  
...  
Keyword(s):  
Prospect Theory ◽  
Value Function ◽  
Probability Weighting ◽  
The Relationship ◽  
The Value Function

scholarly journals NeoCoV Is Closer to MERS-CoV than SARS-CoV

2020 ◽  
Vol 13 ◽  
pp. 117863372093071
Author(s):  
Mohamed M Hassan ◽  
Mohamed A Hussain ◽  
Sumaya Kambal ◽  
Ahmed A Elshikh ◽  
Osama R Gendeel ◽  
...  
Keyword(s):  
Amino Acids ◽  
Maximum Likelihood ◽  
Phylogenetic Trees ◽  
Chemical Properties ◽  
Structural Formula ◽  
Likelihood Method ◽  
Evolutionary Changes ◽  
Whole Genomes ◽  
Physical And Chemical ◽  
The Relationship

Recently, Coronavirus has been given considerable attention from the biomedical community based on the emergence and isolation of a deadly coronavirus infecting human. To understand the behavior of the newly emerging MERS-CoV requires knowledge at different levels (epidemiologic, antigenic, and pathogenic), and this knowledge can be generated from the most related viruses. In this study, we aimed to compare between 3 species of Coronavirus, namely Middle East Respiratory Syndrome (MERS-CoV), Severe Acute Respiratory Syndrome (SARS-CoV), and NeoCoV regarding whole genomes and 6 similar proteins (E, M, N, S, ORF1a, and ORF1ab) using different bioinformatics tools to provide a better understanding of the relationship between the 3 viruses at the nucleotide and amino acids levels. All sequences have been retrieved from National Center for Biotechnology Information (NCBI). Regards to target genomes’ phylogenetic analysis showed that MERS and SARS-CoVs were closer to each other compared with NeoCoV, and the last has the longest relative time. We found that all phylogenetic methods in addition to all parameters (physical and chemical properties of amino acids such as the number of amino acid, molecular weight, atomic composition, theoretical pI, and structural formula) indicated that NeoCoV proteins were the most related to MERS-CoV one. All phylogenetic trees (by both maximum-likelihood and neighbor-joining methods) indicated that NeoCoV proteins have less evolutionary changes except for ORF1a by just maximum-likelihood method. Our results indicated high similarity between viral structural proteins which are responsible for viral infectivity; therefore, we expect that NeoCoV sooner may appear in human-related infection.

Comparison of Weights of Twin Fetuses and of their Incisors

1970 ◽  
Vol 19 (1-2) ◽  
pp. 79-79 ◽  
Author(s):  
M. V. Stack
Keyword(s):  
Maximum Likelihood ◽  
Statistical Model ◽  
Fortran Program ◽  
Maximum Likelihood Estimates ◽  
Additional Parameter ◽  
Growth Status ◽  
Body Weights ◽  
The Relationship

Weights of developing incisors in 10 pairs of twin fetuses have previously been related to ages in order to compare dental growth status (Stack, 1963). Ages (T0) at which weights (W) of mineralised portions of teeth of the temporary dentition become significant have been computed (Stack, 1968), using a Fortran program giving maximum likelihood estimates of the required parameters, based on the statistical model of Angleton and Pettus (1966).Availability of the additional parameter T0 allows a reexamination of the previous data, now fortified by observations on incisors from five further pairs of twin fetuses. Estimates of ages were made from the relationship (T—T0) = k·W½, where values for upper and lower central incisors were 2.0 and 2.8 for k, 19.5 and 18.5 for T0, respectively. Less reliable estimates were obtained from the lateral incisors. These values were computed from observations on 40 dentitions from normal singleton fetuses. Ages were also estimated from tabulated body weights (Documenta Geigy).

Strong Consistency of Maximum Likelihood Estimators in Extreme-Maximum-Value Distribution Model

2014 ◽  
Vol 525 ◽  
pp. 671-676
Author(s):  
Chang Ming Yin ◽  
Bo Hong Chen ◽  
Shuang Hua Liu
Keyword(s):  
Maximum Likelihood ◽  
Strong Consistency ◽  
Maximum Likelihood Estimators ◽  
Value Distribution ◽  
Maximum Likelihood Estimates ◽  
Distribution Model ◽  
Parameter Vector ◽  
Mild Conditions ◽  
Maximum Value ◽  
Strongly Consistent

For the extreme-maximum-value distribution model, we show that maximum likelihood estimates of regression parameter vector is asymptotically existence and strongly consistent under mild conditions

scholarly journals An algorithm for the assessment of several small rates

2012 ◽  
Vol 53 ◽  
Author(s):  
Leonidas Sakalauskas ◽  
Ingrida Vaičiulytė
Keyword(s):  
Maximum Likelihood ◽  
Bayesian Approach ◽  
Maximum Likelihood Method ◽  
Rare Events ◽  
Maximum Likelihood Estimates ◽  
Likelihood Method ◽  
Model Parameters ◽  
Unknown Parameters ◽  
Empirical Bayesian ◽  
Empirical Bayesian Approach

The present paper describes the empirical Bayesian approach applied in the estimation of several small rates. Modeling by empirical Bayesian approach the probabilities of several rare events, it is assumed that the frequencies of events follow to Poisson’s law with different parameters, which are correlated Gaussian random values. The unknown parameters are estimated by the maximum likelihood method computing the integrals appeared here by Hermite–Gauss quadratures. The equations derived that are satisfied by maximum likelihood estimates of model parameters.

scholarly journals Inverse Lomax-Exponentiated G (IL-EG) Family of Distributions: Properties and Applications

2020 ◽  
pp. 48-64
Author(s):  
Jamilu Yunusa Falgore ◽  
Sani Ibrahim Doguwa
Keyword(s):  
Maximum Likelihood ◽  
Maximum Likelihood Method ◽  
Moment Generating Function ◽  
Maximum Likelihood Estimates ◽  
Likelihood Method ◽  
Data Sets ◽  
Baseline Model ◽  
New Family ◽  
Family Of Distributions ◽  
Better Than

A new generator of continuous distributions called the Inverse Lomax-Exponentiated G family, which has three extra positive parameters is proposed. The structural properties of the new family that holds for any continuous baseline model including explicit density function expressions, moments, inequality measurements, moment generating function, reliability functions, Renyi and Shanon entropies, and distribution of order statistics are derived. A Monte Carlo simulation to test the efficiency of the maximum likelihood estimates is conducted. The application of the new sub-model to the two data sets using the maximum likelihood method indicates that the new model is better than the existing competitors.

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