Statistiche e Big Data binomial

Come modellare la somma delle variabili casuali di Bernoulli per i dati dipendenti?

Ho quasi le stesse domande come questa: come posso modellare in modo efficiente la somma delle variabili casuali di Bernoulli? Ma l'impostazione è abbastanza diversa: S=∑i=1,NXiS=∑i=1,NXiS=\sum_{i=1,N}{X_i} , , ~ 20, ~ 0.1P(Xi=1)=piP(Xi=1)=piP(X_{i}=1)=p_iNNNpipip_i Abbiamo i dati per i risultati delle variabili casuali di Bernoulli: ,Xi,jXi,jX_{i,j}Sj=∑i=1,NXi,jSj=∑i=1,NXi,jS_j=\sum_{i=1,N}{X_{i,j}} Se stimiamo la con la stima …

9 distributions modeling binomial random-variable non-independent

Calcola la curva ROC per i dati

Quindi, ho 16 prove in cui sto cercando di autenticare una persona da un tratto biometrico usando Hamming Distance. La mia soglia è impostata su 3,5. I miei dati sono di seguito e solo la versione di prova 1 è un vero positivo: Trial Hamming Distance 1 0.34 2 0.37 …

9 mathematical-statistics roc classification cross-validation pac-learning r anova survival hazard machine-learning data-mining hypothesis-testing regression random-variable non-independent normal-distribution approximation central-limit-theorem interpolation splines distributions kernel-smoothing r data-visualization ggplot2 distributions binomial random-variable poisson-distribution simulation kalman-filter regression lasso regularization lme4-nlme model-selection aic r mcmc dlm particle-filter r panel-data multilevel-analysis model-selection entropy graphical-model r distributions quantiles qq-plot svm matlab regression lasso regularization entropy inference r distributions dataset algorithms matrix-decomposition regression modeling interaction regularization expected-value exponential gamma-distribution mcmc gibbs probability self-study normality-assumption naive-bayes bayes-optimal-classifier standard-deviation classification optimization control-chart engineering-statistics regression lasso regularization regression references lasso regularization elastic-net r distributions aggregation clustering algorithms regression correlation modeling distributions time-series standard-deviation goodness-of-fit hypothesis-testing statistical-significance sample binary-data estimation random-variable interpolation distributions probability chi-squared predictor outliers regression modeling interaction

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