
pec
 Referenced in 5 articles
[sw15816]
 package pec: Prediction Error Curves for Risk Prediction Models in Survival Analysis. Validation of risk ... predictions obtained from survival models and competing risk models based on censored data using inverse...

BayesMendel
 Referenced in 4 articles
[sw11022]
 BayesMendel: an R environment for Mendelian risk prediction. Several important syndromes are caused by deleterious ... variant of these genes, and to predict the risk of disease for that individual, using ... information on his/her family history. Mendelian risk prediction models accomplish these goals by integrating Mendelian...

mstate
 Referenced in 26 articles
[sw04376]
 hazard estimation and prediction with AalenJohansen or simulation in competing risks and multistate...

GAS
 Referenced in 4 articles
[sw17726]
 ValueatRisk Prediction in R with the GAS Package. GAS models have been recently ... signal extraction and prediction. This paper details how financial risk managers ... models for ValueatRisk (VaR) prediction using the novel GAS package for R. Details...

riskRegression
 Referenced in 2 articles
[sw19175]
 package riskRegression. Risk Regression Models and Prediction Scores for Survival Analysis with Competing Risks. Implementation ... assessing and comparing performance of risk predictions (risk markers and risk prediction models). Prediction performance ... deal with right censored data. Lists of risk markers and lists of risk models ... repeatedly splits the data, trains the risk prediction models on one part of each split...

BeCoDiS
 Referenced in 7 articles
[sw15918]
 CoDiS: a mathematical model to predict the risk of human diseases spread between countries  validation ... studies the ability of the model in predicting the EVD evolution between countries starting from...

Zelig
 Referenced in 9 articles
[sw17526]
 such as relative risk ratios, average treatment effects, first differences and predicted and expected values...

saa
 Referenced in 1 article
[sw20966]
 Integrative genetic risk prediction using nonparametric empirical Bayes classification. Genetic risk prediction ... sizes of the studies on which the prediction algorithms are trained. One way to increase ... approach to integrative genetic risk prediction of complex diseases with binary phenotypes. It accommodates possible...

AdaGrad
 Referenced in 87 articles
[sw22202]
 haystacks in the form of very predictive but rarely seen features. Our paradigm stems from ... give several efficient algorithms for empirical risk minimization problems with common and important regularization functions...

PleioGRiP
 Referenced in 1 article
[sw10197]
 PleioGRiP: Pleiotropic Genetic Risk Prediction via Bayesian model search and classification. The program PleioGRiP performs ... classifiers can be used for genetic risk prediction, either selecting the classifier with optimal number...

obliqueRSF
 Referenced in 1 article
[sw31325]
 data indicate that the ORSF’s predicted risk function has high prognostic value in comparison ... highlight characteristics of its tenyear predicted risk function for atherosclerotic cardiovascular disease events (ASCVD...

wally
 Referenced in 1 article
[sw31334]
 wally: The Wally Calibration Plot for Risk Prediction Models. A prediction model is calibrated ... among all subjects that have a predicted risk of x%. A calibration plot provides...

AgenaRisk
 Referenced in 6 articles
[sw07338]
 AgenaRisk solution includes predictive analytics and scales up to organisationallevel risk monitoring and assessment...

PredictABEL
 Referenced in 0 articles
[sw15384]
 package PredictABEL: Assessment of Risk Prediction Models. PredictABEL includes functions to assess the performance ... such as risk distributions, ROC curves, calibration plot, discrimination box plot and predictiveness curves ... unweighted risk scores as well as predicted risks using logistic regression analysis. These logistic regression...

PARTRAC
 Referenced in 2 articles
[sw18319]
 paves the way for superior predictions of radiation risks...

DecisionCurve
 Referenced in 0 articles
[sw16393]
 population impact of adopting a risk prediction instrument into clinical practice. Given one or more ... instruments (risk models) that predict the probability of a binary outcome, this package calculates ... threshold used to categorize observations as ’high risk.’ Curves can be estimated using data from...

CASPAR
 Referenced in 6 articles
[sw12242]
 CASPAR: a hierarchical bayesian approach to predict survival times in cancer from gene expression data ... different risk classes, however, relatively little has been done with respect to the prediction...

bmrm
 Referenced in 18 articles
[sw11016]
 minimization of convex and nonconvex risk under L1 or L2 regularization. Implements the algorithm ... data analysis. The applications includes: structured prediction, linear SVM, multiclass SVM, fbeta optimization...

survJamda
 Referenced in 1 article
[sw13830]
 methods or metaanalysis to predict patients’ survival and risk assessment...

CrystallBall
 Referenced in 7 articles
[sw06509]
 leading spreadsheetbased application for predictive modeling, forecasting, simulation, and optimization. It gives you unparalleled ... insight into the critical factors affecting risk. With Crystal Ball, you can make the right...