Pertanyaan yang diberi tag variogram

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Bagaimana cara melakukan imputasi nilai dalam jumlah poin data yang sangat besar?

Saya memiliki dataset yang sangat besar dan sekitar 5% nilai acak hilang. Variabel-variabel ini berkorelasi satu sama lain. Contoh berikut dataset R hanyalah contoh mainan dengan data berkorelasi dummy. set.seed(123) # matrix of X variable xmat <- matrix(sample(-1:1, 2000000, replace = TRUE),...

r random-forest missing-data data-imputation multiple-imputation large-data definition moving-window self-study categorical-data econometrics standard-error regression-coefficients normal-distribution pdf lognormal regression python scikit-learn interpolation r self-study poisson-distribution chi-squared matlab matrix r modeling multinomial mlogit choice monte-carlo indicator-function r aic garch likelihood r regression repeated-measures simulation multilevel-analysis chi-squared expected-value multinomial yates-correction classification regression self-study repeated-measures references residuals confidence-interval bootstrap normality-assumption resampling entropy cauchy clustering k-means r clustering categorical-data continuous-data r hypothesis-testing nonparametric probability bayesian pdf distributions exponential repeated-measures random-effects-model non-independent regression error regression-to-the-mean correlation group-differences post-hoc neural-networks r time-series t-test p-value normalization probability moments mgf time-series model seasonality r anova generalized-linear-model proportion percentage nonparametric ranks weighted-regression variogram classification neural-networks fuzzy variance dimensionality-reduction confidence-interval proportion z-test r self-study pdf
8
Masalah dengan kriging biasa

Saya mengikuti artikel wiki ini yang berhubungan dengan kriging biasa Sekarang matriks kovarians saya terlihat seperti ini, untuk 4 variabel 1 0.740818220681718 0.548811636094027 0.406569659740599 0.740818220681718 1 0.740818220681718 0.548811636094027 0.548811636094027 0.740818220681718 1...

covariance autocorrelation variogram