Dominasi makna tradisi pada pola tata massa dan ruang luar arsitektur hunian …
Mengingat kondisi geografis Indonesia yang berada di area utama cincin gunung api pasifik, maka bencana alam adalah hal yang kemungkinan besar akan terjadi di kemudian hari. Sedangkan proyek reha…
Approximating Partial Likelihood Estimators via Optimal Subsampling
With the growing availability of large-scale biomedical data, it is often time-consuming or infeasible to directly perform traditional statistical analysis with relatively limited computing resourc…
A Unified Approach to Variable Selection for Partially Linear Models
We focus on the general partially linear model without any structure assumption on the nonparametric component. For such a model with both linear and nonlinear predictors being multivariate, we pro…
Optical Flow in the Dark
Optical flow estimation in low-light conditions is a challenging task for existing methods and current optical flow datasets lack low-light samples. Even if the dark images are enhanced before esti…
The Grid Bootstrap for Continuous Time Models
his article proposes the new grid bootstrap to construct confidence intervals (CI) for the persistence parameter in a class of continuous-time models. It is different from the standard grid bootstr…
Long Memory Factor Model : On Estimation of Factor Memories
This article considers the estimation of the integration orders of the latent factors in an approximate factor model. Both the common factors and idiosyncratic error terms are potentially nonstatio…
Bayesian Stochastic Gradient Descent for Stochastic Optimization with Streami…
We consider stochastic optimization under distributional uncertainty, where the unknown distributional parameter is estimated from streaming data that arrive sequentially over time. Moreover, data …
Matching Using Sufficient Dimension Reduction for Causal Inference
To estimate causal treatment effects, we propose a new matching approach based on the reduced covariates obtained from sufficient dimension reduction. Compared with the original covariates and the …
Identification of Time-Varying Factor Models
The emergence of large datasets with long time spans has cast doubt on the assumption of constant loadings in conventional factor models. Being a potential solution, the time-varying factor model (…
Bayesian Tree-Structured Two-Level Clustering for Nested Data Analysis
ata integration plays a crucial role in the era of big data. The nested data are a combined set of observations from multiple sources and exhibit heterogeneity both at the source level and at the o…
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