# Draw one sample of the underlying GP responses for a partially censored Gaussian process using sequential nearest neighbor (SNN) method ```r rptmvn( y, cens_lb, cens_ub, mask_cens, m = 30, covmat = NULL, locs = NULL, cov_name = NULL, cov_parm = NULL, NN = NULL, ordering = 0, seed = NULL ) ``` ## Arguments - `y`: uncensored responses of length n, where n is the number of all responses - `cens_lb`: lower bound vector for TMVN of length n - `cens_ub`: upper bound vector for TMVN of length n - `mask_cens`: mask for censored responses (also locations) of length n - `m`: positive integer for the number of nearest neighbors used - `covmat`: n-by-n dense covariance matrix, either `covmat` or `locs`, `cov_name`, and `cov_parms` need to be provided - `locs`: location matrix n X d - `cov_name`: covariance function name from the `GpGp` package - `cov_parm`: parameters for the covariance function from the `GpGp` package - `NN`: n X m matrix for nearest neighbors. i-th row is the nearest neighbor indices of y_i. `NN[i, 1]` should be `i` - `ordering`: `0` for do not reorder, `1` for variance descending order, `2` for maximin ordering - `seed`: set seed for reproducibility ## Returns a vector of length n representing the underlying GP responses ## Examples ```r library(GpGp) library(RANN) library(nntmvn) set.seed(123) x <- matrix(seq(from = 0, to = 1, length.out = 51), ncol = 1) cov_name <- "matern15_isotropic" cov_parm <- c(1.0, 0.1, 0.001) #' variance, range, nugget cov_func <- getFromNamespace(cov_name, "GpGp") covmat <- cov_func(cov_parm, x) y <- t(chol(covmat)) %*% rnorm(length(x)) mask <- y < 0.3 y_cens <- y y_cens[mask] <- NA lb <- rep(-Inf, 100) ub <- rep(0.3, 100) m <- 10 y_samp_mtd1 <- rptmvn(y_cens, lb, ub, mask, m = m, locs = x, cov_name = cov_name, cov_parm = cov_parm, seed = 123 ) y_samp_mtd2 <- rptmvn(y_cens, lb, ub, mask, m = m, covmat = covmat, seed = 123 ) plot(x, y_cens, ylim = range(y)) points(x[mask, ], y[mask], col = "blue") plot(x, y_cens, ylim = range(y)) points(x[mask, ], y_samp_mtd1[mask], col = "red") plot(x, y_cens, ylim = range(y)) points(x[mask, ], y_samp_mtd2[mask], col = "brown") ```

rptmvn function