Hypothetical Set Research Articles

Towards Efficiency in the Residual and Parametric Bootstrap Techniques

There are many bootstrap methods that can be used for statistical analysis especially in econometrics, biometrics, Statistics, Sampling and so on. The sole aim of this paper is to ascertain the accuracy and efficiency of the estimates from the independent and identically distributed (iid) simple linear regression (SLR) model under a variety of assessment conditions using bootstrap techniques. Analysis was carried out using S-plus statistical package on hypothetical data sets from a normal distribution with different group proficiency levels to buttress the arguments in the paper. In the course of the analysis, 268,800 scenarios were replicated 1000 times. The result shows a significant difference between the performances of the bootstrap methods used, namely; residual and parametric bootstrap techniques. From the analysis, the largest bias and standard error were always associated with model HP311 while the smallest bias and standard error values were associated with models HR311. The exception was found in the group proficiency level 3- N (1, 0.25), when the sample sizes were 200, 1000 and 10000 instead of model HR311 producing the smallest bias and standard error, model RP311 did. The significantly better performance of the residual bootstrap indicates the possible use of this technique in assessment of comparative performance and the capability of yielding very accurate, consistent, faster and extra-ordinarily reliable statistical inference under several assessment conditions.

Dynamics of a Nonautonomous SIR Model with Time-Varying Impulsive Release and General Nonlinear Incidence Rate in a Polluted Environment

In a polluted environment, considering the biological population infected with a kind of disease and hunted by human beings, we formulate a nonautonomous SIR population-epidemic model with time-varying impulsive release and general nonlinear incidence rate and investigate dynamical behaviors of the model. Under the reasonable assumptions, the sufficient conditions which guarantee the globally attractive of the disease-free periodic solution and the permanence of the infected fish are established, that is, the infected fish dies out if , whereas the disease persists if . To substantiate our theoretical results, extensive numerical simulations are performed for a hypothetical set of parameter values.

그룹 가치스코어 모형을 활용한 강수확률예보의 사용자 만족도 효용 분석

This study proposes a mathematical model to estimate the economic value of weather forecast service, among which the precipitation forecast service is focused. The value is calculated in terms of users' satisfaction or dissatisfaction resulted from the users' decisions made by using the precipitation probabilistic forecasts and thresholds. The satisfaction values can be quantified by the traditional value score model, which shows the scaled utility values relative to the perfect forecast information. This paper extends the value score concept to a collective value score model which is defined as a weighted sum of users' satisfaction based on threshold distribution in a group of the users. The proposed collective value score model is applied to the picnic scenario by using four hypothetical sets of probabilistic forecasts, i.e., under-confident, over-confident, under-forecast and over-forecast. The application results show that under-confident type of forecasts outperforms the others as a measure of the maximum collective value regardless of users' dissatisfaction patterns caused by two types of forecast errors, e.g., miss and false alarm.

A coordinated European Union minimum wage policy?

This article contributes to the growing debate on minimum wage coordination at European Union (EU) level. We consider the introduction of a hypothetical EU-wide minimum set at 60 percent of the median wage in each European country; we compare the diverse minimum wage-setting systems across Europe and discuss how they could be affected by such policy. The institutional impact of this European common threshold would be larger in those countries where minimum wages are currently collectively agreed by social partners than in those countries where they are set by statutory regulation. But according to our statistical analysis, such EU-wide minimum wage would affect a larger proportion of the workforce in those countries with statutory minimum wages, since they tend to have a larger low-paid segment of employment.

Differences between hypothetical and experience-based value sets for EQ-5D used in Sweden: Implications for decision makers

A number of value sets are available today for converting EQ-5D questionnaire responses to quality-adjusted life year-weights used in health economic evaluations. The aim of this study is to analyse the differences between the commonly used hypothetical UK value set and the newly introduced Swedish experience-based value set and to evaluate health economic implications of such differences on policy decisions. Differences between the two value sets were studied using two methods: a comparison of health states and improvements as well as an empirical comparison. In the comparison of health states and improvements, the valuations of all EQ-5D states and all pure improvements were compared. In the empirical study, a database of 23,925 individuals was used to identify patient groups that could be affected by the implementation of the Swedish experience-based value set. The comparison of health states and possible improvements showed that only three health states were assigned a lower quality-adjusted life year-weight and most improvements were given smaller absolute values if the experience-based value set was used. The empirical comparison showed that severe conditions were assigned higher values when using the experience-based value set. The Swedish experience-based value set seems to render a higher estimated level of health-related quality of life in virtually all health conditions compared to the hypothetical UK value set. In extension, health-related quality of life enhancing interventions are likely to be given higher priority in decision-making situations where hypothetical values are used to construct quality-adjusted life year-weights. In situations where experience-based quality-adjusted life year-weights are used, life-prolonging interventions would be prioritised.

Dynamic analysis of time fractional order phytoplankton–toxic phytoplankton–zooplankton system

In this paper, we study the dynamics of a time fractional order toxic-phytoplankton–phytoplankton–zooplankton system (TPPZS). Routh–Hurwitz criteria is applied to discuss the stability analysis of biologically feasible equilibrium points for the given system in terms of reproduction numbers (associated with ecological as well as disease phenomena). Local stability properties of the toxic-phytoplankton-free equilibrium are also investigated. Numerical simulations are performed for a hypothetical set of parameter values in support of our analytic results.

Treatment preferences of originator versus biosimilar drugs in Crohn’s disease; discrete choice experiment among gastroenterologists

Objective. To explore preferences of gastroenterologists for biosimilar drugs in Crohn’s disease. Material and methods. Discrete choice experiment was carried out involving 51 Hungarian gastroenterologists in May 2014. The following attributes were used to describe hypothetical choice sets: 1) type of the treatment (biosimilar/originator), 2) severity of disease, 3) availability of continuous medicine supply, 4) frequency of the efficacy check-ups. Multinomial logit model was used to differentiate between three attitude types: 1) always opting for the originator, 2) willing to consider biosimilar for biological-naïve patients only, 3) willing to consider biosimilar treatment for both types of patients. Conditional logit model was used to estimate the probabilities of choosing a given profile. Results. Men, senior consultants, working in inflammatory bowel disease center and treating more patients were more likely willing to consider biosimilar for biological-naïve patients only. Treatment type (originator/biosimilar) was the most important determinant of choice for patients already treated with biologicals, and the availability of continuous medicine supply in case of biological-naïve patients. The probabilities of choosing the biosimilar with all the benefits offered over the originator under current reimbursement conditions are 89% versus 11% for new patients, and 44% versus 56% for patients already treated with biological. Conclusions. For gastroenterologist, the continuous medical supply would be one of the major benefits of biosimilars. However, benefits offered in the scenarios do not compensate for the change from the originator to the biosimilar treatment of patients already treated with biologicals.

Evaluation of adaptation strategies under A2 climate change scenario using InfoCrop model for kharif maize in middle Gujarat region

Thirty years (2071-2100) projected climatic data under A2 scenario along with thirty years (1961-1990) actual observed data suitably adjusted to the baseline period were used for climate change impact study on maize cultivars (GM-3 and GS-2) in Dahod district of middle Gujarat. For purpose of evaluating different adaptation options, different realistic hypothetical set of crop management data such as additional irrigation, fertilizer and organic manure were used using InfoCrop model. It was found that two supplementary irrigations given at tasseling and silking stages increased 18 per cent yield over rainfed maize when it was sown during first July for cv. GS-2. The application of additional dose of chemical fertilizer (50 per cent extra) and organic manure + chemical fertilizer (50 per cent) at knee height and tesseling stages gave 10 and 8 per cent higher yield, respectively.

The persistence of prey-predator model with competition hosts

<p>In this paper, the conditions of the occurrence of persistence of a mathematical model consists from four-species Syn- Ecosymbiosis involves a competition hosts for prey are established. Finally, in order to confirm our obtained analytical results, numerical simulations have been done for a hypothetical set of parameter values.</p>

Present Sense Impression and Excited Utterance Hearsay Exceptions: Interesting Application Questions

Rules 803(1) and 803(2) of the Federal Rules of Evidence provide as follows:The following are not excluded by the rule against hearsay, regardless of whether the declarant is available as a witness:(1) Present Sense Impression. A statement describing or explaining an event or condition, made while or immediately after the declarant perceived it.(2) Excited Utterance. A statement relating to a startling event or condition, made while the declarant was under the stress of excitement that it caused.The article explores with respect to the present sense impression and excited utterance hearsay exceptions by means of a hypothetical set of questions how, if at all, the admissibility of hearsay statements preferred pursuant to said exceptions is affected by contentions relating to unidentified bystander, absence of corroboration, res gestae, stress of excitement, and bad faith.

Evaluating Wine-Tasting Results and Randomness with a Mixture of Rank Preference Models

AbstractEvaluating observed wine-tasting results as a mixture distribution, using linear regression on a transformation of observed results, has been described in the wine-tasting literature. This article advances the use of mixture models by considering that existing work, examining five analyses of ranking and mixture model applications to non-wine food tastings and then deriving a mixture model with specific application to observed wine-tasting results. The mixture model is specified with Plackett-Luce probability mass functions, solved with the expectation maximization algorithm that is standard in the literature, tested on a hypothetical set of wine ranks, tested with a random-ranking Monte Carlo simulation, and then employed to evaluate the results of a blind tasting of Pinot Gris by experienced tasters. The test on a hypothetical set of wine ranks shows that a mixture model is an accurate predictor of observed rank densities. The Monte Carlo simulation yields confirmatory results and an estimate of potential Type I errors (the probability that tasters appear to agree although ranks are actually random). Application of the mixture model to the tasting of Pinot Gris, with over a 95% level of confidence based on the likelihood ratio and t statistics, shows that agreement among tasters exceeds the random expectation of illusory agreement. (JEL Classifications: A10, C10, C00, C12, D12)

Analysis of Prey – Predator System with Prey Population Experiencing Critical Depensation Growth Function

In this paper we have presented a pair of coupled differential equations to represent a prey – predator system. It is assumed that the growth of the prey population follows critical depensation function and that of the predator population is negative in absence of the prey population. The critical depensation function is special since the growth rate is negative initially but positive later on. This function is stable both at the origin and at the carrying capacity while unstable at the critical mass quantity. The maximum and minimum rates of the critical depensation model are verified. It can be interpreted here that the prey represent fish and the predator represent a kind of birds that mostly feeding on fish to live. We showed the solution of the model is positive and bounded. The mathematical model of the system consisting of 7 parameters is constructed and shown that the non – dimensionalization decreases the number of model parameters to 4. The deterministic behavior of the model around feasible equilibrium points and criteria of the interior positive equilibrium points and their stability are explained. The trivial equilibrium point is always stable while the two axial equilibrium points and the lone interior equilibrium point are either stable or unstable depending on the conditions imposed on the parameters. The criterion for the existence of the limit cycle and the region of existence of interior equilibrium point are identified. Global stability of interior equilibrium points is also studied. For the interior equilibrium point of the model (i) the region of existence is identified (ii) Dulac’s criteria is applied to find the limit cycle and (iii) Lyaponov function is used to analyze the global stability. Simulation study of the model is conducted in support of the analytical analysis. To solidify the analytical results numerical simulations are provided for hypothetical set of parametric values.

Sensitivity analysis of reference evapotranspiration to sensor accuracy

Meteorological sensor networks are often used across agricultural regions to calculate the ASCE Standardized Reference Evapotranspiration (ET) Equation, and inaccuracies in individual sensors can lead to inaccuracies in ET estimates. Multiyear datasets from the semi-arid Colorado Agricultural Meteorological (CoAgMet) and humid Florida Automated Weather Network (FAWN) networks were evaluated using a local sensitivity analysis (LSA) method which calculated the total error range of each individual sensor, as well as Morris and eFAST global sensitivity analysis (GSA) methods which simultaneously evaluated the full accuracy range of each sensor. Sensitivity of inputs (i.e., temperature, humidity, wind speed, and solar radiation) generally had values within the same range for the FAWN network with solar radiation being the most influential input in the summer, while sensitivity to wind speed for the CoAgMet network was much higher than the other inputs. Due to its simplicity and ease of application, LSA is suggested as a minimal screening method for evaluating input sensor sensitivity. GSA results were highly correlated with each other, but local sensitivity was poorly correlated to GSA methods regarding wind input in Colorado. Uncertainty analysis showed the current configuration of sensors in the CoAgMet network to have a higher range of ET values between 5% and 95% confidence intervals, as compared to the FAWN network. The eFAST GSA method was applied using a hypothetical set of “best case” sensors in both stations (i.e., sensors with the best accuracy between both sites), showing solar radiation to be the most influential input in the high ET months of summer, and the sensitivity in Colorado to wind to be vastly decreased, suggesting that the CoAgMet network could benefit from an upgrade to more accurate anemometers.

Differences Between Hypothetical and Experience-Based Value Sets for Eq-5d: Implications for Decision Makers.

Differences Between Hypothetical and Experience-Based Value Sets for Eq-5d: Implications for Decision Makers.

The script concordance test for clinical reasoning: re-examining its utility and potential weakness.

The script concordance test (SCT) assesses clinical reasoning under conditions of uncertainty. Relatively little information exists on Z-score (standard deviation [SD]) cut-offs for distinguishing more experienced from less experienced trainees, and whether scores depend on factual knowledge. Additionally, a recent review highlighted the finding that the SCT is potentially weakened by the fact that the mere avoidance of extreme responses may greatly increase test scores. This study was conducted in order to elucidate the best cut-off Z-scores, to correlate SCT scores with scores on a separate medical knowledge examination (MKE), and to investigate potential solutions to the weakness of the SCT. An analysis of scores on pulmonary and critical care medicine tests undertaken during July and August 2013 was performed. Clinical reasoning was tested using 1-hour SCTs (Question Sets 1 or 2). Medical knowledge was tested using a 3-hour, computer-adapted, multiple-choice question examination. The expert panel was composed of 16 attending physicians. The SCTs were completed by 16 fellows and 10 residents. Fourteen fellows completed the MKE. Test reliability was acceptable for both Question Sets 1 and 2 (Cronbach's alphas of 0.79 and 0.89, respectively). Z-scores of -2.91 and -1.76 best separated the scores of residents from those of fellows, and the scores of fellows from those of attending physicians, respectively. Scores on the SCT and MKE were poorly correlated. Simply avoiding extreme answers boosted the Z-scores of the lowest 10 scorers on both Question Sets 1 and 2 by ≥1SD. Increasing the proportion of questions with extreme modal answers to 50%, and using hypothetical question sets created from Question Set 1 overcame this problem, but consensus scoring did not. The SCT was able to differentiate between test subjects of varying levels of competence, and results were not associated with medical knowledge. However, the test was vulnerable to responses that intentionally avoided extreme values. Increasing the proportion of questions with extreme modal answers may attenuate the effect of candidates exploiting the test weakness related to extreme responses.

The stability of a perturbed eco-epidemiological model with Holling type II functional response by white noise

In this paper, we have proposed and analyzed a perturbed eco-epidemiological model with Holling type II functional response by white noise. By Lyapunov analysis methods, we prove the stochastic stability, its long time behavior around the equilibrium of deterministic eco-epidemiological model and the stochastic asymptotic stability. Numerical simulations for a hypothetical set of parameter values are presented to illustrate the analytical findings.

Plumbdads and Quarkles: Discussing Modeling Trends with Students Using Fictional Parameters

Helping students develop an understanding of how to interpret experimental data trends is an important part of the introductory physics laboratory. Unfortunately, many of my colleagues have lamented that too many of their students do this poorly. This is a common refrain, and past research has already revealed student difficulties with measurement, uncertainty, and the overall meaning of data.1–3 Like many instructors, I prefer discovery-style labs and in many laboratory investigations students are asked to use curve-fitting tools to discover a relationship.4 But one day in lab, I began to wonder if students were looking at data and curve fitting in a way profoundly different than scientists. Research already indicates significant differences,5,6 but to get a clearer understanding of how students would treat general data, a hypothetical set of data using fictional parameters (plumbdads and quarkles) was given to first day students.

Insilico analysis of hypothetical proteins unveils putative metabolic pathways and essential genes in Leishmania donovani.

Leishmaniasis is a parasitic disease caused by the protozoan Leishmania, which is active in two broad forms namely, Visceral Leishmaniasis (VL or Kala Azar) and Cutaneous Leishmaniasis (CL). The disease is most prevalent in the tropical regions and poses a threat to over 70 countries across the globe. About 200 million people are estimated to be at risk of developing VL in the Indian subcontinent, and this refers to around 67% of the global VL disease burden. The Indian state of Bihar alone accounts for 50% of the total VL cases. While no vaccination exists, several pentavalent antimonials and drugs like Paromomycin, Amphotericin, Miltefosine etc. are used in the treatment of Leishmaniasis. However, due to their low efficacies and the resistance developed by the bug to these medications, there is an urgent need to look into newer species specific targets. The proteome information available suggests that among the 7960 proteins in Leishmania donavani, a staggering 65% remains classified as a hypothetical uncharacterized set. In this background, we have attempted to assign probable functions to these hypothetical sequences present in this parasite, to explore their plausible roles as druggable receptors. Thus, putative functions have been defined to 105 hypothetical proteins, which exhibited a GO term correlation and PFAM domain coverage of more than 50% over the query sequence length. Of these, 27 sequences were found to be associated with a reference pathway in KEGG as well. Further, using homology approaches, four pathways viz., Ubiquinone biosynthesis, Fatty acid elongation in Mitochondria, Fatty Acid Elongation in ER and Seleno-cysteine Metabolism have been reconstructed. In addition, 7 new putative essential genes have been mined with the help of Eukaryotic Database of Essential Genes (DEG). All these information related to pathways and essential genes indeed show promise for exploiting the select molecules as potential therapeutic targets.

A new halo-independent approach to dark matter direct detection analysis

Uncertainty in the local dark matter velocity distribution is a key difficulty in the analysis of data from direct detection experiments. Here we propose a new approach for dealing with this uncertainty, which does not involve any assumptions about the structure of the dark matter halo. Given a dark matter model, our method yields the velocity distribution which best describes a set of direct detection data as a finite sum of streams with optimised speeds and densities. The method is conceptually simple and numerically very efficient. We give an explicit example in which the method is applied to determining the ratio of proton to neutron couplings of dark matter from a hypothetical set of future data.

Persisting challenges in multiple models: a note on commonly unnoticed issues regarding collinearity and spatial structure of ecological data

There is a growing need to heed some caveats in numerical data analysis. In 2013, I set out some issues regarding multiple regression frameworks. Here, I used both hypothetical and real data sets collected in Brazil to discuss the implications of, and provide suggestions for, some statistical issues regarding to collinearity and spatial structure of ecological data. For example, a weak treatment of collinearities might lead to discarding important variables for the model, and this can be avoided by a correct approach to collinearities before the model selection. Moreover, studies have demonstrated that the spatial structure in both predictor and response variables is an important point to be addressed, rather than the presence of this structure only in the residuals. Aiming to facilitate the controlling of such bias, I provide two fully explained scripts for R language. Considering the seriousness of spatial structure, my opinion is that no article that presents confirmatory analysis should be considered for publication if their authors do not heed that caveat; facing this issue, I strongly suggest that one performs a variance partitioning scheme.