Pertanyaan yang diberi tag predictive-models

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Nilai variabel tersembunyi regresi linear R "bernilai"

Ini hanya contoh yang saya temui beberapa kali, jadi saya tidak punya data sampel. Menjalankan model regresi linier di R: a.lm = lm(Y ~ x1 + x2) x1adalah variabel kontinu. x2bersifat kategorikal dan memiliki tiga nilai, mis. "Rendah", "Sedang" dan "Tinggi". Namun output yang diberikan oleh R akan...

r regression categorical-data regression-coefficients categorical-encoding machine-learning random-forest anova spss r self-study bootstrap monte-carlo r multiple-regression partitioning neural-networks normalization machine-learning svm kernel-trick self-study survival cox-model repeated-measures survey likert correlation variance sampling meta-analysis anova independence sample assumptions bayesian covariance r regression time-series mathematical-statistics graphical-model machine-learning linear-model kernel-trick linear-algebra self-study moments function correlation spss probability confidence-interval sampling mean population r generalized-linear-model prediction offset data-visualization clustering sas cart binning sas logistic causality regression self-study standard-error r distributions r regression time-series multiple-regression python chi-squared independence sample clustering data-mining rapidminer probability stochastic-processes clustering binary-data dimensionality-reduction svd correspondence-analysis data-visualization excel c# hypothesis-testing econometrics survey rating composite regression least-squares mcmc markov-process kullback-leibler convergence predictive-models r regression anova confidence-interval survival cox-model hazard normal-distribution autoregressive mixed-model r mixed-model sas hypothesis-testing mediation interaction
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Mengapa Anova () dan drop1 () memberikan jawaban berbeda untuk GLMM?

Saya memiliki GLMM formulir: lmer(present? ~ factor1 + factor2 + continuous + factor1*continuous + (1 | factor3), family=binomial) Ketika saya menggunakan drop1(model, test="Chi"), saya mendapatkan hasil yang berbeda daripada jika saya menggunakan Anova(model, type="III")dari paket mobil atau...

r anova glmm r mixed-model bootstrap sample-size cross-validation roc auc sampling stratification random-allocation logistic stata interpretation proportion r regression multiple-regression linear-model lm r cross-validation cart rpart logistic generalized-linear-model econometrics experiment-design causality instrumental-variables random-allocation predictive-models data-mining estimation contingency-tables epidemiology standard-deviation mean ancova psychology statistical-significance cross-validation synthetic-data poisson-distribution negative-binomial bioinformatics sequence-analysis distributions binomial classification k-means distance unsupervised-learning euclidean correlation chi-squared spearman-rho forecasting excel exponential-smoothing binomial sample-size r change-point wilcoxon-signed-rank ranks clustering matlab covariance covariance-matrix normal-distribution simulation random-generation bivariate standardization confounding z-statistic forecasting arima minitab poisson-distribution negative-binomial poisson-regression overdispersion probability self-study markov-process estimation maximum-likelihood classification pca group-differences chi-squared survival missing-data contingency-tables anova proportion
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Model Sejarah Acara Diskrit-Waktu (Bertahan Hidup) di R

Saya mencoba menyesuaikan model waktu-diskrit dalam R, tapi saya tidak yakin bagaimana melakukannya. Saya telah membaca bahwa Anda dapat mengatur variabel dependen dalam baris yang berbeda, satu untuk setiap pengamatan waktu, dan menggunakan glmfungsi dengan logit atau tautan cloglog. Dalam hal...

r survival pca sas matlab neural-networks r logistic spatial spatial-interaction-model r time-series econometrics var statistical-significance t-test cross-validation sample-size r regression optimization least-squares constrained-regression nonparametric ordinal-data wilcoxon-signed-rank references neural-networks jags bugs hierarchical-bayesian gaussian-mixture r regression svm predictive-models libsvm scikit-learn probability self-study stata sample-size spss wilcoxon-mann-whitney survey ordinal-data likert group-differences r regression anova mathematical-statistics normal-distribution random-generation truncation repeated-measures variance variability distributions random-generation uniform regression r generalized-linear-model goodness-of-fit data-visualization r time-series arima autoregressive confidence-interval r time-series arima autocorrelation seasonality hypothesis-testing bayesian frequentist uninformative-prior correlation matlab cross-correlation