• We are collecting empirical temperature climate data to develop local models describing stream temperature and streamflows in headwater streams in Spread Creek, a Tributary to the Upper Snake River, WY. (usgs.gov)
  • Empirical evaluation of the competing models was performed using model selection criteria and goodness-of-fit through simulation. (bmj.com)
  • Using DNA data from 50 nuclear loci sequenced in African, Asian and Native American samples, we show here by extensive simulations that a simple African replacement model with exponential growth has a higher probability (78%) as compared with alternative multiregional evolution or assimilation scenarios. (pnas.org)
  • However, because past demographic events are likely to have greatly affected current patterns of genetic diversity, genetic data are difficult to interpret without a general demographic model that can explain neutral variability ( 3 ). (pnas.org)
  • To evaluate examiner variability in a superficial skin marker model of canine stifle kinematics. (biomedsearch.com)
  • This is an important step towards improving the reliability of predictive models in precision medicine and assisting the development of individualised treatments. (meduniwien.ac.at)
  • This authoritative, state-of-the-art reference is ideal for graduate students, researchers and practitioners in business and finance seeking to broaden their skills of understanding of econometric time series models. (ecampus.com)
  • Working professionals, researchers, or students who are familiar with R and basic statistical techniques such as linear regression and who want to learn how to use R to perform more advanced analytics. (springer.com)
  • Through consulting at Elkhart Group Limited and former work at the UCLA Statistical Consulting Group, he has supported a wide array of clients ranging from graduate students, to experienced researchers, and biotechnology companies. (springer.com)
  • Researchers involved in the study have devised a statistical model to enable the weight of fingerprint evidence to be quantified, paving the way for its full inclusion in the criminal identification process. (redorbit.com)
  • NEW YORK: A novel statistical model that can accurately predict the time and duration of floods has been developed by researchers, including one of Indian origin. (dailyexcelsior.com)
  • Researchers said the model can help mitigate potential risk imposed by longer duration floods on critical infrastructure systems such as flood control dams, bridges and power plants. (dailyexcelsior.com)
  • Researchers at Carnegie Mellon University have developed a new dynamic statistical model to visualize changing patterns in networks, including gene expression during developmental periods of the brain. (phys.org)
  • Published in the Proceedings of the National Academy of Sciences , the model now gives researchers a tool that extends past observing static networks at a single snapshot in time, which is hugely beneficial since network data are usually dynamic. (phys.org)
  • Via external validation, an independent dataset can assess how well the model performs. (nih.gov)
  • This provides readers the information necessary to assess the bias in a study, compare other published models, and determine the model's clinical usefulness. (nih.gov)
  • How to assess whether a model fits data well? (le.ac.uk)
  • Thus, for any estimated model, it is a simple matter to look at these indices in relation to tabled values of the noncentral chi-square distribution in order to assess power. (gsu.edu)
  • A series of chromatographic response functions were proposed and implemented in order to assess and validate the models. (mdpi.com)
  • field components may be modeled as narrow band random processes. (ni.com)
  • Today's Significance paper, which publishes in advance of the full study in the Journal of the Royal Statistical Society: Series A later this year, highlights this subjectivity in current processes, calling for changes in the way such key evidence is allowed to be presented. (redorbit.com)
  • Modeling strategies that omit interactions may result in misleading estimates of absolute treatment benefit for individual patients with the potential hazard of suboptimal decision making. (nih.gov)
  • how do we turn parameter estimates into model predictions? (coursera.org)
  • Statistical models have been proven to help organisations make decisions based on predictions across the customer life cycle. (experian.co.uk)
  • Sometimes, though, we are able to compare model predictions with real data - predicted sales versus actual sales, for example. (kdnuggets.com)
  • However, statistical predictions are always subject to a certain range of variation. (meduniwien.ac.at)
  • Just a couple of general comments: (1) Any model that makes probabilistic predictions can be judged on its own terms by comparing to actual data. (andrewgelman.com)
  • Several metrics were used to characterize the accuracy of the predictions, and in some cases the best--performing model as judged by one metric was not the best performer when judged by another metric. (osti.gov)
  • When there is incomplete science to prescribe which inputs should be included in a model of reliability to predict future trends, statistical model/variable selection techniques can be leveraged on a stockpile or population of units to improve reliability predictions as well as suggest new mechanisms affecting reliability to explore. (osti.gov)
  • Spatial patterns of predictions by the final, 1SE BRT model agreed reasonably well with previously observed patterns of nitrate occurrence in groundwater of the Central Valley. (usgs.gov)
  • A statistical model is presented for computing probabilities that proteins are present in a sample on the basis of peptides assigned to tandem mass (MS/MS) spectra acquired from a proteolytic digest of the sample. (nih.gov)
  • Using peptide assignments to spectra generated from a sample of 18 purified proteins, as well as complex H. influenzae and Halobacterium samples, the model is shown to produce probabilities that are accurate and have high power to discriminate correct from incorrect protein identifications. (nih.gov)
  • Logistic regression modeling technique was used to clarify the relationship among probabilities of minor, serious, fatal injury risk to the rider, and the influence of risk factors in accidents involving opposing vehicle contact point, motorcycle contact point, opposing vehicle speed, motorcycle speed, relative heading angle of impact, and helmet use. (sae.org)
  • We present a probabilistic extension of logic programs below that allows for both relational probabilistic models and compact descriptions of conditional probabilities. (ubc.ca)
  • A relational probability model ( RPM ) or probabilistic relational model is a model in which the probabilities are specified on the relations, independently of the actual individuals. (ubc.ca)
  • The biomarkers identified in this way can then be used to develop models to predict the subgroups of patients for whom treatment with a newly developed drug will be more effective than the standard treatment. (meduniwien.ac.at)
  • Three steps were presented to be used in developing a model to predict exposure levels of ethylene-oxide (75218) (EtO) in the sterilization industry. (cdc.gov)
  • In addition, the UMass team will develop, implement, and evaluate a model that predicts relations in a similarly integrated way and will extend the integrated model to predict events along with coreference and relations. (umass.edu)