Department of Statistics & Data Science, UCLA
Parent: UCLA
eScholarship stats: History by Item for April through July, 2026
| Item | Title | Total requests | 2026-07 | 2026-06 | 2026-05 | 2026-04 |
|---|---|---|---|---|---|---|
| 5f3177k0 | SOCRE: Statistics Online Computational Resource for Education | 861 | 103 | 215 | 203 | 340 |
| 6d28n81g | Counting the Homeless in Los Angeles County | 733 | 8 | 154 | 558 | 13 |
| 27s1d3h7 | Robust Statistical Modeling Using the t- Distribution | 693 | 138 | 182 | 188 | 185 |
| 6vh9k0cf | Probabilistic Evaluation of Counterfactual Queries | 676 | 283 | 149 | 128 | 116 |
| 80d1k93n | Decoding heterogeneous single-cell perturbation responses | 558 | 119 | 160 | 163 | 116 |
| 4mw725pz | scDesign2: a transparent simulator that generates high-fidelity single-cell gene expression count data with gene correlations captured | 548 | 20 | 55 | 440 | 33 |
| 2mk8r49v | Comparative Fit Indices in Structural Models | 508 | 170 | 85 | 133 | 120 |
| 0mg8m7g6 | Data Moves | 504 | 89 | 121 | 168 | 126 |
| 9030v001 | Multilevel varying coefficient spatiotemporal model | 466 | 88 | 114 | 157 | 107 |
| 6gv9n38c | Causal Diagrams for Empirical Research | 439 | 102 | 111 | 110 | 116 |
| 0jz5p8kk | Understanding Responses of Summer Continental Daily Temperature Variance to Perturbations in the Land Surface Evaporative Resistance | 429 | 64 | 115 | 158 | 92 |
| 067331ns | How, and For Whom, Does Higher Education Increase Voting? | 398 | 42 | 78 | 148 | 130 |
| 0pg6471b | Making sense of sensitivity: extending omitted variable bias | 397 | 67 | 96 | 136 | 98 |
| 4q74x3fr | The Foundations of Causal Inference | 391 | 92 | 70 | 135 | 94 |
| 20d438mm | PseudotimeDE: inference of differential gene expression along cell pseudotime with well-calibrated p-values from single-cell RNA sequencing data | 367 | 63 | 99 | 91 | 114 |
| 0rn9t5jv | An Unexpected Decline in Spring Atmospheric Humidity in the Interior Southwestern United States and Implications for Forest Fires | 360 | 67 | 97 | 105 | 91 |
| 4sk26297 | Show Me the Missing Data | 354 | 50 | 89 | 118 | 97 |
| 583610fv | A Generalized Definition of the Polychoric Correlation Coefficient | 349 | 47 | 88 | 110 | 104 |
| 7qp4604r | The Phi-coefficient, the Tetrachoric Correlation Coefficient, and the Pearson-Yule Debate | 349 | 71 | 71 | 98 | 109 |
| 6cn677bx | Comparative Fit Indices in Structural Models | 338 | 51 | 84 | 98 | 105 |
| 6db1b6df | Cerebral amyloid-beta plaques link host genotypes to neurocognitive impairment among HIV-infected adults | 334 | 118 | 71 | 82 | 63 |
| 3m13p4nn | Direct and indirect effects | 319 | 62 | 65 | 95 | 97 |
| 6gr648np | Benchmarking Computational Doublet-Detection Methods for Single-Cell RNA Sequencing Data | 319 | 73 | 85 | 74 | 87 |
| 3141h70c | Scaling Corrections for Statistics in Covariance Structure Analysis | 307 | 82 | 53 | 101 | 71 |
| 19r9k47z | Use of a Reproducible R Shiny Web App to Promote Students' Interest in Coding | 294 | 29 | 66 | 105 | 94 |
| 8940b4k8 | Approximating the Distribution of Pareto Sums | 292 | 46 | 92 | 64 | 90 |
| 0hf5z4t4 | Bayesian Geostatistics Using Predictive Stacking | 284 | 42 | 69 | 102 | 71 |
| 65z429wc | Assessment and Propagation of Model Uncertainty | 282 | 87 | 45 | 92 | 58 |
| 4mx2r10v | An integrated encyclopedia of DNA elements in the human genome | 273 | 34 | 70 | 86 | 83 |
| 331047wt | Characterizing Bias in Population Genetic Inferences from Low-Coverage Sequencing Data | 272 | 28 | 67 | 80 | 97 |
| 7qw8m94p | The Farm Animal Genotype–Tissue Expression (FarmGTEx) Project | 267 | 50 | 102 | 55 | 60 |
| 0tg4t8bd | Recent Developments in Causal Inference and Machine Learning | 266 | 23 | 65 | 79 | 99 |
| 0xz2k6c9 | A regime shift in seasonal total Antarctic sea ice extent in the twentieth century | 264 | 39 | 70 | 93 | 62 |
| 3925v2s7 | Statistics or biology: the zero-inflation controversy about scRNA-seq data | 256 | 59 | 55 | 92 | 50 |
| 4h2796b8 | scReadSim: a single-cell RNA-seq and ATAC-seq read simulator | 254 | 24 | 93 | 64 | 73 |
| 32f943tq | Technical Introduction: A Primer on Probabilistic Inference | 252 | 17 | 24 | 193 | 18 |
| 45x689gq | Identifiability of Path-Specific Effects | 251 | 43 | 54 | 86 | 68 |
| 07f7p3q3 | Dynamic Bayesian Learning for Spatiotemp oral Mechanistic Models | 248 | 41 | 61 | 78 | 68 |
| 3tv1b3bg | Transportability across studies: A formal approach | 245 | 64 | 34 | 97 | 50 |
| 3xn518nr | Systematic evaluation of methylation-based cell type deconvolution methods for plasma cell-free DNA | 245 | 60 | 58 | 68 | 59 |
| 53n4f34m | Bayesian networks | 242 | 51 | 50 | 77 | 64 |
| 9q6553kr | Object Perception as Bayesian Inference | 242 | 69 | 41 | 52 | 80 |
| 87t603ns | On Statistical Criteria: Theory, History, and Applications | 241 | 28 | 52 | 75 | 86 |
| 6qg1r096 | Cooling of US Midwest summer temperature extremes from cropland intensification | 240 | 54 | 53 | 72 | 61 |
| 7j01t5sf | On the Relation Between the Polychoric Correlation Coefficient and Spearman's Rank Correlation Coefficient | 239 | 70 | 43 | 62 | 64 |
| 4x788631 | A Comparison of Maximum-Likelihood and Asymptotically Distribution-Free Methods of Treating Incomplete Non-Normal Data | 235 | 116 | 17 | 68 | 34 |
| 8pm5v0f8 | Highly Scalable Bayesian Geostatistical Modeling via Meshed Gaussian Processes on Partitioned Domains | 234 | 23 | 67 | 82 | 62 |
| 38m3m5pq | On Principal Hessian Directions for Data Visualization and Dimension Reduction: Another Application of Stein's Lemma | 233 | 40 | 58 | 70 | 65 |
| 66f206ff | Causal Machine Learning: A Deductive–Inductive Framework for Sociological Research | 233 | 21 | 53 | 100 | 59 |
| 0v46r5w8 | The Causal Mediation Formula – A practitioner guide to the assessment of causal pathways | 227 | 53 | 69 | 52 | 53 |
Note: Due to the evolving nature of web traffic, the data presented here should be considered approximate and subject to revision. Learn more.