Non parametric
On Parametric (and Non-Parametric) Variation
... The theory of PV hypothesizes that the range of choices is ‘antecedently known’, and this basic property correlates with a number of others which distinguish PV from non-parametric variation, and allow us ...
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Gnostics in Valuation: Non Parametric Approach to Multiples Estimation
... methodological questions in adjusting the multiples to the particular industry. In this paper, we identify the most accurate method of estimation of the multiples for the business valuation. Extensive secondary ...
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Bayesian non parametric inference for Λ coalescents : posterior consistency and a parametric method
... Bayesian non-parametric inference of the Λ-measure of Λ-coalescent processes with recurrent mutation, parametrised by probability measures on the unit ...any non-trivial prior is inconsistent when ...
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Parametric methods outperformed non-parametric methods in comparisons of discrete numerical variables
... data. Non-parametric methods – which were outperformed by their parametric counterparts in our study–were the most commonly used statistical meth- ...standard parametric methods for continuous ...
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Association between Parametric and Non-Parametric Stability Models in Multi-Location Trials of Pakistan
... The parametric stability parameters follow the assumptions of distribution while non-parametric stability parameters do not require any assumption and have advantage over parametric that they ...
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Technical Efficiency of Maize Production in Nigeria: Parametric and Non-Parametric Approach
... The Data Envelopment Analysis (DEA) was developed by Charnes, Cooper, and Rhodes (1978). It involved the estimation of non- parametric frontiers. Other than comparing efficiency across Decision Making Units ...
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A non parametric investigation of risk premia
... standard non-parametric kernel regres- sion ...however, non-parametric analysis is more difficult due to increased computational costs and, more fundamentally, to a problem known as the curse ...
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A non parametric investigation of risk premia
... the non-parametric model of this ...The non-parametric model is good at capturing features of the actual series, but its performance worsens in the middle years of the sample ...
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A Non Parametric Approach to Spatial Causality
... The purpose of this paper is to show the capacity of a new non-parametric test based on symbolic entropy and symbolic dynamics to deal with the detection of linear and non-linear spatial causality. ...
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Non Parametric Bayesian Areal Linguistics
... name non-parametric models. The idea behind non- parametric models is that one does not commit a pri- ori to a particularly number of ...modeling, non-parametric distributions ...
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A non parametric ACD model
... fully non parametric way resides in the unobservability of one or some ...bivariate non parametric regression technique, which means that it performs better than the deconvolution kernel and ...
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Parametric versus non-parametric statistics in the analysis of randomized trials with non-normally distributed data
... Background: It has generally been argued that parametric statistics should not be applied to data with non-normal distributions. Empirical research has demonstrated that Mann-Whitney ge[r] ...
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Parametric and non-parametric analysis of tax changes
... to note that this specification typically allows only the model’s intercept to shift across the categorical variables. In principle, we should allow all parameters in the model to vary over all realizations of the ...
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Evaluating the Relative Efficiency of Iran's Tourism Industry: A Non-Parametric Approach
... The parametric method was first introduced by Lovell and Schmit, and Bayer, 1988; Shahabinejad et ...model. Parametric methods include stochastic frontier approach (SFA), thick frontier approach (TFA), and ...
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Statistical methods and modelling techniques for analysing hospital readmission of discharged psychiatric patients: a systematic literature review
... As the usability of statistical tests always depends on the population size of the data, we analysed the number of patients under observation. Studies with larger popula- tion sizes featured survival analysis (median ...
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Mixing in Some Knowledge: Enriched Context Patterns for Bayesian Word Sense Induction
... Bayesian topic models have recently been shown to perform well in word sense in- duction (WSI) tasks. Such models have al- most exclusively used bag-of-words features, and failed to attain improvement by includ- ing ...
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Tail dependence in emerging ASEAN-6 equity markets: empirical evidence from quantitative approaches
... Furthermore, we evaluated structural interdependence by different methodologies, using both non-parametric and parametric copulas (traditional and time-varying). We come to a conclusion that copulas ...
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Biodiversity and scale : determinants of species richness in Great Smoky Mountains National Park
... environmental dissimilarity.. Figure 5.3 Estimated species richness of trees in GSMNP with increasing sample size for a) parametric and non-parametric estimators and b) the turnover-ba[r] ...
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Financial Fraud Detection Model Based on Random Forest
... The Random Forest model have a high accuracy reaching 88%. In order to compare its accuracy with other methods as well as parameter models and nonparametric models. This study established several other detection models ...
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Trend Analysis of Monthly and Annual Temperature Series of Quetta, Pakistan
... In the present study, the monthly average temperature of Quetta – Pakistan is examined. Quetta is the provincial capital of Balochistan, the largest province of Pakistan in terms of area. Quetta is located in the West of ...
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