PEMODELAN REGRESI RIDGE ROBUST S,M, MM-ESTIMATOR DALAM PENANGANAN MULTIKOLINIERITAS DAN PENCILAN (Studi Kasus : Faktor-Faktor yang Mempengaruhi Kemiskinan di Jawa Tengah Tahun 2020)

The Ordinary Least Squares (OLS) is one of the most commonly used method to estimate linier regression parameters. If there is a violation of assumptions such as multicolliniearity especially coupled with the outliers, then the regression with OLS is no longer used. One method can be used to solved the multicollinearity and outliers problem is Ridge Robust Regression. Ridge Robust Regression is a modification of ridge regression method used to solve the multicolliniearity and using some estimators of robust regression used to solve the outlier, the estimator including : Maximum likelihood estimator (M-estimator), Scale estimator (S-estimator), and Method of moment estimator (MM-estimator). The case study can be used with this method is data with multicollinearity and outlier, the case study in this research is poverty in Central Java 2020 influenced by life expentancy, unemployment number, GRDP rate, dependency ratio, human development index, the precentage of population over 15 years of age with the highest education in primary school, mean years school. The result of estimation using OLS show that there is a multicollinearity and presence an outliers. Applied the ridge robust regression to case study prove that ridge robust regression can improve parameter estimation. The best ridge robust regression model is Ridge Robust Regression S-Estimator. The influence value of predictor variabels to poverty is 73,08% and the MSE value is 0,00791.

The Implementation And Application Of Firm Valuation Models

<span style="font-family: &quot;Times New Roman&quot;,&quot;serif&quot;; font-size: 10pt; mso-fareast-font-family: 'Times New Roman'; mso-fareast-language: EN-US; mso-ansi-language: DA; mso-bidi-language: AR-SA;" lang="DA">This study focuses on methodological errors that arise when firm valuation is carried out in practice. Violation of assumptions underlying the valuation models are examples of methodological errors. We analyze valuation spreadsheets from five Danish financial institutions (i.e., stockbrokers and corporate finance departments) in order to trace if firm valuation models are properly applied. We conclude the following: (i) Methodological errors often cause valuation models to generate estimates that differ significantly from the theoretically correct value; and (ii) Firm value estimates were biased due to a variety of methodological errors. The implications of those errors may be significant. Investors are exposed to poor recommendations. Financial institutions such as investment bankers and stockbrokers may be exposed to bad reputation and lawsuits. Accounting firms that do not carry out firm valuation correctly (for example in testing goodwill for impairment) also run the risk of litigations.</span><p>&nbsp;</p>

Meta-Analysis for Evidence Synthesis in Plant Pathology: An Overview

Meta-analysis is the analysis of the results of multiple studies, which is typically performed in order to synthesize evidence from many possible sources in a formal probabilistic manner. In a simple sense, the outcome of each study becomes a single observation in the meta-analysis of all available studies. The methodology was developed originally in the social sciences by Smith, Glass, Rosenthal, Hunter, and Schmidt, based on earlier pioneering contributions in statistics by Fisher, Pearson, Yates, and Cochran, but this approach to research synthesis has now been embraced within many scientific disciplines. However, only a handful of articles have been published in plant pathology and related fields utilizing meta-analysis. After reviewing basic concepts and approaches, methods for estimating parameters and interpreting results are shown. The advantages of meta-analysis are presented in terms of prediction and risk analysis, and the high statistical power that can be achieved for detecting significant effects of treatments or significant relationships between variables. Based on power considerations, the fallacy of naïve counting of P values in a narrative review is demonstrated. Although there are many advantages to meta-analysis, results can be biased if the analysis is based on a nonrepresentative sample of study outcomes. Therefore, novel approaches for characterizing the upper bound on the bias are discussed, in order to show the robustness of meta-analysis to possible violation of assumptions.

Completeness of notification of tuberculosis in The Netherlands: how reliable is record-linkage and capture–recapture analysis?

SUMMARYThe aim of this study was to describe a systematic process of record-linkage, cross-validation, case-ascertainment and capture–recapture analysis to assess the quality of tuberculosis registers and to estimate the completeness of notification of incident tuberculosis cases in The Netherlands in 1998. After record-linkage and cross-validation 1499 tuberculosis patients were identified, of whom 1298 were notified, resulting in an observed under-notification of 13·4%. After adjustment for possible imperfect record-linkage and remaining false-positive hospital cases observed under-notification was 7·3%. Log-linear capture–recapture analysis initially estimated a total number of 2053 (95% CI 1871–2443) tuberculosis cases, resulting in an estimated under-notification of 36·8%. After adjustment for possible imperfect record-linkage and remaining false-positive hospital cases various capture–recapture models estimated under-notification at 13·6%. One of the reasons for the higher than expected estimated under-notification in a country with a well-organized system of tuberculosis control might be that some tuberculosis cases, e.g. extrapulmonary tuberculosis, are managed by clinicians less familiar with notification of infectious diseases. This study demonstrates the possible impact of violation of assumptions underlying capture–recapture analysis, especially the perfect record-linkage, perfect positive predictive value and absent three-way interaction assumptions.

Joint estimation of sampling and turnover rates from fossil databases: capture-mark-recapture methods revisited

The estimation and interpretation of temporal patterns in origination and extinction rates is a major goal of paleobiology. However, the possibility of coincident variation in the quality and completeness of the fossil record makes the identification of such patterns particularly difficult. Previously, Nichols and Pollock (1983) proposed that capture-mark-recapture (CMR) models be adapted to address this problem. These models can be used to estimate both sampling and turnover rates, reducing the risk of confounding the two quantities. Since that time, theoretical advances have made possible the application of these tools to a much broader range of problems. This paper reviews those advances likely to be of greatest relevance in paleobiological studies. They include (1) joint estimation of per-taxon origination and extinction rates, (2) modeling sampling or turnover rates as explicit functions of causal variables, (3) ranking of alternative models according to their fit to the data, and (4) estimation of parameter values using multiple models. These are illustrated by application to an Ordovician database of benthic marine genera from key higher taxa. Robustness of these methods to violation of assumptions likely to be suspect in paleobiological studies further suggests that these models can make an important contribution to the quantitative study of macroevolutionary dynamics.

Estimating Migration Rates for Pacific Herring (Clupea pallasi) Using Tag-Recovery Data

Tag-recovery data can be used to estimate migration rates among a set of strata provided that both tagging and recoveries occur on all the strata over a number of years. The model formulation described here is a simple matrix extension of a tag-recovery experiment where individual recaptures are replaced by a matrix of recoveries representing movement between release and recovery sites. Derived parameters of emigration, immigration, and overall net survival can also be estimated. The models are applied to estimate the migration of Pacific herring (Clupea pallasi) between spawning grounds in the Prince Rupert District and Central District of British Columbia. Effects of the violation of assumptions and aspects of the planning of capture–recapture experiments are also presented.

The Calibration of a Sit-ups Task Using the Rasch Poisson Counts Model

The purpose of this study was to calibrate a nationally used sit-ups test using the Rasch Poisson Counts model and evaluate the model-data fit. The total number of subjects was 8,723, consisting of 4,486 girls and 4,237 boys, ages 10 to 18. The estimated difficulty of the sit-ups task was −2.80, which was appropriate for a majority of examinees whose ability levels ranged from.09 to 1.39. After the calibration, boys and girls as well as different age groups were compared under the same metric. Graphs of the model-data fit demonstrated that the model-data fit at a low ability level was not as good as the fit at a high ability, which could be caused by violation of assumptions of the model that examinees have the same performance speed throughout the test and that the speed at a given time is independent of the number of sit-ups completed so far. Key words: item response theory, modeling of motor performance, fitness testing