Elements of Large-Sample Theory

Interval Estimation for a Binomial Proportion

Brown, L. D., Cai, T., & Dasgupta, A. (2001) · Statistical Science · doi:10.1214/ss/1009213286 · Cited by 3,622 · see citing works

Untitled work

Tufford (2017) · doi:10.1007/s · Cited by 2,003 · see citing works

Wilcoxon-Mann-Whitney or t-test? On assumptions for hypothesis tests and multiple interpretations of decision rules

Fay, M. P., & Proschan, M. A. (2010) · Statistics Surveys · doi:10.1214/09-ss051 · Cited by 1,121 · see citing works

Phase 1 Trial of Malaria Transmission Blocking Vaccine Candidates Pfs25 and Pvs25 Formulated with Montanide ISA 51

Wu, Y., Ellis, R. D., Shaffer, D., Fontes, E., Malkin, E. M., Mahanty, S., Fay, M. P., Narum, D. L., Rausch, K. M., Miles, A. P., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0002636 · Cited by 447 · see citing works

Partitioning linear trends in age-adjusted rates

Hankey, B. F., Ries, L. A. G., Kosary, C. L., Feuer, E. J., Merrill, R. M., Clegg, L. X., & Edwards, B. K. (2000) · Cancer Causes & Control · doi:10.1023/a:1008953201688 · Cited by 425 · see citing works

ModDrop: Adaptive Multi-Modal Gesture Recognition

Neverova, N., Wolf, C., Taylor, G., & Nebout, F. (2016) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2015.2461544 · Cited by 420 · see citing works

Minimax Optimal Procedures for Locally Private Estimation

Duchi, J. C., Jordan, M. I., & Wainwright, M. J. (2017) · Journal of the American Statistical Association · doi:10.1080/01621459.2017.1389735 · Cited by 390 · see citing works

Models for Estimating Abundance from Repeated Counts of an Open Metapopulation

Dail, D., & Madsen, L. J. (2010) · Biometrics · doi:10.1111/j.1541-0420.2010.01465.x · Cited by 384 · see citing works

Even More Efficient Quantum Computations of Chemistry Through Tensor Hypercontraction

Lee, J., Berry, D. W., Gidney, C., Huggins, W. J., McClean, J. R., Wiebe, N., & Babbush, R. (2021) · PRX Quantum · doi:10.1103/prxquantum.2.030305 · Cited by 304 · see citing works

Evaluating the heritability explained by known susceptibility variants: a survey of ten complex diseases

So, H.-C., Gui, A. H. S., Cherny, S. S., & Sham, P. C. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20579 · Cited by 289 · see citing works

Nonparametric rank tests for event studies

Kolari, J. W., & Pynnönen, S. (2011) · Journal of Empirical Finance · doi:10.1016/j.jempfin.2011.08.003 · Cited by 267 · see citing works

Operating characteristics of the rank‐based inverse normal transformation for quantitative trait analysis in genome‐wide association studies

McCaw, Z. R., Lane, J. M., Saxena, R., Redline, S. S., & Lin, X. (2019) · Biometrics · doi:10.1111/biom.13214 · Cited by 255 · see citing works

Bearing remaining useful life prediction using support vector machine and hybrid degradation tracking model

Yan, M., Wang, X., Wang, B., Chang, M., & Muhammad, I. (2019) · ISA Transactions · doi:10.1016/j.isatra.2019.08.058 · Cited by 245 · see citing works

Local asymptotics for polynomial spline regression

Huang, J. Z. (2003) · The Annals of Statistics · doi:10.1214/aos/1065705120 · Cited by 226 · see citing works

Upstream Innovation and Product Variety in the U.S. Home PC Market

Eizenberg, A. (2014) · The Review of Economic Studies · doi:10.1093/restud/rdu004 · Cited by 207 · see citing works

Reputation and Strength of Ties in Predicting Commercial Success and Artistic Merit of Independents in the Italian Feature Film Industry*

Delmestri, G., Montanari, F., & Usai, A. (2005) · Journal of Management Studies · doi:10.1111/j.1467-6486.2005.00529.x · Cited by 194 · see citing works

Discrete Bids and Empirical Inference in Divisible Good Auctions

Kastl, J. (2011) · The Review of Economic Studies · doi:10.1093/restud/rdq024 · Cited by 187 · see citing works

Effects of management communication, opportunity for learning, and work schedule flexibility on organizational commitment

Ng, T. W. H., Butts, M. M., Vandenberg, R. J., DeJoy, D. M., & Wilson, M. G. (2006) · Journal of Vocational Behavior · doi:10.1016/j.jvb.2005.10.004 · Cited by 181 · see citing works

Estimation of the Mean of Functional Time Series and a Two-Sample Problem

Horvath, L. H., Kokoszka, P. S., & Reeder, R. (2012) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.1467-9868.2012.01032.x · Cited by 174 · see citing works

Introduction to Mathematical Statistics

Sylvan, D. (2013) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2013.756334 · Cited by 169 · see citing works

An interactive meta-analysis of MRI biomarkers of myelin

Mancini, M., Karakuzu, A., Cohen‐Adad, J., Cercignani, M., Nichols, T. E., & Stikov, N. (2020) · eLife · doi:10.7554/elife.61523 · Cited by 160 · see citing works

Asymptotic Normality of the QMLE Estimator of ARCH in the Nonstationary Case

Jensen, S., & Rahbek, A. (2004) · Econometrica · doi:10.1111/j.1468-0262.2004.00504.x · Cited by 146 · see citing works

Simulating Sensitivities of Conditional Value at Risk

Hong, L. J., & Liu, G. (2008) · Management Science · doi:10.1287/mnsc.1080.0901 · Cited by 143 · see citing works

Directed Information Graphs

Quinn, C. J., Kiyavash, N., & Coleman, T. P. (2015) · IEEE Transactions on Information Theory · doi:10.1109/tit.2015.2478440 · Cited by 143 · see citing works

Bayesian rank-based hypothesis testing for the rank sum test, the signed rank test, and Spearman's ρ

van Doorn, J. B., Ly, A., Marsman, M., & Wagenmakers, E. (2020) · Journal of Applied Statistics · doi:10.1080/02664763.2019.1709053 · Cited by 147 · see citing works

Hypothesis tests for population heterogeneity in meta‐analysis

Viechtbauer, W. (2006) · British Journal of Mathematical and Statistical Psychology · doi:10.1348/000711005x64042 · Cited by 136 · see citing works

On the Asymptotic Validity of Fully Sequential Selection Procedures for Steady-State Simulation

Kim, S., & Nelson, B. L. (2006) · Operations Research · doi:10.1287/opre.1060.0281 · Cited by 135 · see citing works

Bias in Whole Genome Amplification: Causes and Considerations

Sabina, J., & Leamon, J. H. (2015) · Methods in molecular biology · doi:10.1007/978-1-4939-2990-0_2 · Cited by 129 · see citing works

Cluster–Robust Variance Estimation for Dyadic Data

Aronow, P. M., Samii, C., & Assenova, V. (2015) · Political Analysis · doi:10.1093/pan/mpv018 · Cited by 128 · see citing works

Direct Prediction Methods on Lifetime Distribution of Organic Light-Emitting Diodes From Accelerated Degradation Tests

Park, J. I., & Bae, S. J. (2010) · IEEE Transactions on Reliability · doi:10.1109/tr.2010.2040761 · Cited by 126 · see citing works

Multidimensional Adaptive Testing with Optimal Design Criteria for Item Selection

Mulder, J., & van der Linden, W. J. (2008) · Psychometrika · doi:10.1007/s11336-008-9097-5 · Cited by 123 · see citing works

Assessing the inter-rater agreement for ordinal data through weighted indexes

Marasini, D., Quatto, P., & Ripamonti, E. (2014) · Statistical Methods in Medical Research · doi:10.1177/0962280214529560 · Cited by 116 · see citing works

Multidimensional Adaptive Testing with Constraints on Test Content

Veldkamp, B. P., & van der Linden, W. J. (2002) · Psychometrika · doi:10.1007/bf02295132 · Cited by 114 · see citing works

Age‐conditional probabilities of developing cancer

Fay, M. P., Pfeiffer, R. M., Cronin, K. A., Le, C., & Feuer, E. J. (2003) · Statistics in Medicine · doi:10.1002/sim.1428 · Cited by 107 · see citing works

Detecting human influence on extreme temperatures in China

Wen, Q. H., Zhang, X., Xu, Y., & Wang, B. (2013) · Geophysical Research Letters · doi:10.1002/grl.50285 · Cited by 105 · see citing works

Conditional Monte Carlo Estimation of Quantile Sensitivities

Fu, M. C., Hong, L. J., & Hu, J.-Q. (2009) · Management Science · doi:10.1287/mnsc.1090.1090 · Cited by 96 · see citing works

The inverse-probability-of-censoring weighting (IPCW) adjusted win ratio statistic: an unbiased estimator in the presence of independent censoring

Dong, G., Mao, L., Huang, B., Gamalo, M., Wang, J., Yu, G., & Hoaglin, D. C. (2020) · Journal of Biopharmaceutical Statistics · doi:10.1080/10543406.2020.1757692 · Cited by 92 · see citing works

Efficient Tests of Stock Return PredictabilityPreprint

Campbell, J. Y., & Yogo, M. (2002) · SSRN Electronic Journal · doi:10.2139/ssrn.343782 · Cited by 92 · see citing works

Efficiency of Generalized Estimating Equations for Binary Responses

Chaganty, N. R., & Joe, H. (2004) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/j.1467-9868.2004.05741.x · Cited by 91 · see citing works

Exponential-Family Models of Random Graphs: Inference in Finite, Super and Infinite Population Scenarios

Schweinberger, M., Krivitsky, P. N., Butts, C. T., & Stewart, J. R. (2020) · Statistical Science · doi:10.1214/19-sts743 · Cited by 90 · see citing works

Correcting for Test Score Measurement Error in ANCOVA Models for Estimating Treatment Effects

Lockwood, J. R., III, & McCaffrey, D. F. (2013) · Journal of Educational and Behavioral Statistics · doi:10.3102/1076998613509405 · Cited by 90 · see citing works

Generic Results for Establishing the Asymptotic Size of Confidence Sets and Tests

Andrews, D. W. K., Cheng, X., & Guggenberger, P. (2011) · Journal of Econometrics · doi:10.1016/j.jeconom.2020.04.027 · Cited by 90 · see citing works

A Paradox from Randomization-Based Causal Inference

Ding, P. (2017) · Statistical Science · doi:10.1214/16-sts571 · Cited by 88 · see citing works

Best Practices for Binary and Ordinal Data Analyses

Verhulst, B., & Neale, M. C. (2021) · Behavior Genetics · doi:10.1007/s10519-020-10031-x · Cited by 88 · see citing works

Testing Mutual Independence in High Dimension via Distance Covariance

Yao, S., Zhang, X., & Shao, X. (2017) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1111/rssb.12259 · Cited by 87 · see citing works

Statistical Tests of Conditional Independence Between Responses and/or Response Times on Test Items

van der Linden, W. J., & Glas, C. A. W. (2009) · Psychometrika · doi:10.1007/s11336-009-9129-9 · Cited by 83 · see citing works

Continuous Dropout

Shen, X., Tian, X., Liu, T., Xu, F., & Tao, D. (2017) · IEEE Transactions on Neural Networks and Learning Systems · doi:10.1109/tnnls.2017.2750679 · Cited by 88 · see citing works

Tests of Statistical Methods for Estimating Galaxy Luminosity Function and Applications to the Hubble Deep Field

Takeuchi, T. T., Yoshikawa, K., & Ishii, T. T. (2000) · The Astrophysical Journal Supplement Series · doi:10.1086/313409 · Cited by 80 · see citing works

Ensembles of Overfit and Overconfident Forecasts

Grushka‐Cockayne, Y., Jose, V. R. R., & Lichtendahl, K. C. (2016) · Management Science · doi:10.1287/mnsc.2015.2389 · Cited by 79 · see citing works

Detecting Answer Copying When the Regular Response Process Follows a Known Response Model

van der Linden, W. J., & Sotaridona, L. S. (2006) · Journal of Educational and Behavioral Statistics · doi:10.3102/10769986031003283 · Cited by 72 · see citing works

Estimation and extrapolation of time trends in registry data — Borrowing strength from related populations

Riebler, A., Held, L., & Rue, H. (2011) · Zurich Open Repository and Archive (University of Zurich) · doi:10.5167/uzh-51391 · Cited by 72 · see citing works

Non-Stationarity in Time-Series Analysis: Modeling Stochastic and Deterministic Trends

Ryan, O., Haslbeck, J. M. B., & Waldorp, L. (2025) · Multivariate Behavioral Research · doi:10.1080/00273171.2024.2436413 · Cited by 68 · see citing works

Decomposing Treatment Effect Variation

Ding, P., Feller, A., & Miratrix, L. W. (2018) · Journal of the American Statistical Association · doi:10.1080/01621459.2017.1407322 · Cited by 68 · see citing works

Gaussian and bootstrap approximations for high-dimensional U-statistics and their applications

Chen, X. (2018) · The Annals of Statistics · doi:10.1214/17-aos1563 · Cited by 65 · see citing works

Win statistics (win ratio, win odds, and net benefit) can complement one another to show the strength of the treatment effect on time‐to‐event outcomes

Dong, G., Huang, B., Verbeeck, J., Cui, Y., Song, J., Gamalo, M., Wang, D., Hoaglin, D. C., Seifu, Y., Mütze, T., et al. (2022) · Pharmaceutical Statistics · doi:10.1002/pst.2251 · Cited by 65 · see citing works

Kernel-Based Methods for Hypothesis Testing: A Unified View

Harchaoui, Z., Bach, F., Cappé, O., & Moulines, É. (2013) · IEEE Signal Processing Magazine · doi:10.1109/msp.2013.2253631 · Cited by 65 · see citing works

Complementarity and Aggregate Implications of Assortative Matching: A Nonparametric Analysis

Graham, B. S., Imbens, G. W., & Ridder, G. (2009) · National Bureau of Economic Research · doi:10.3386/w14860 · Cited by 65 · see citing works

A Non-Central Version of the Birnbaum-Saunders Distribution for Reliability Analysis

Guiraud, P., Leiva, V., & Fierro, R. (2009) · IEEE Transactions on Reliability · doi:10.1109/tr.2008.2011869 · Cited by 63 · see citing works

Estimation and extrapolation of time trends in registry data—Borrowing strength from related populations

Riebler, A., Held, L., & Rue, H. (2012) · The Annals of Applied Statistics · doi:10.1214/11-aoas498 · Cited by 60 · see citing works

Kullback–Leibler Information and Its Applications in Multi-Dimensional Adaptive Testing

Wang, C., Chang, H., & Boughton, K. A. (2010) · Psychometrika · doi:10.1007/s11336-010-9186-0 · Cited by 59 · see citing works

Detecting anomalous deviations from standard maritime routes using the Ornstein-Uhlenbeck process

d'Afflisio, E., Braca, P., Millefiori, L. M., & Willett, P. (2018) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2018.2875887 · Cited by 59 · see citing works

Hybrid multi-step estimators for stochastic differential equations based on sampled data

Kamatani, K., & Uchida, M. (2014) · Statistical Inference for Stochastic Processes · doi:10.1007/s11203-014-9107-4 · Cited by 57 · see citing works

Methodological issues in the assessment of substance use phenotypes

Neale, M. C., Aggen, S. H., MAES, H. H. M., Kubarych, T. S., & Schmitt, J. E. (2006) · Addictive Behaviors · doi:10.1016/j.addbeh.2006.03.047 · Cited by 57 · see citing works

Parameter Estimation From Quantized Observations in Multiplicative Noise Environments

Zhu, J., Lin, X., Blum, R. S., & Gu, Y. (2015) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2015.2436359 · Cited by 50 · see citing works

Joint Sensing and Power Allocation in Nonconvex Cognitive Radio Games: Quasi-Nash Equilibria

Pang, J., & Scutari, G. (2013) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2013.2239993 · Cited by 49 · see citing works

Local Dependence Diagnostics in IRT Modeling of Binary Data

Liu, Y., & Maydeu‐Olivares, A. (2012) · Educational and Psychological Measurement · doi:10.1177/0013164412453841 · Cited by 49 · see citing works

A “placement of death” approach for studies of treatment effects on ICU length of stay

Lin, W. T., Halpern, S. D., Kerlin, M. P., & Small, D. S. (2014) · Statistical Methods in Medical Research · doi:10.1177/0962280214545121 · Cited by 48 · see citing works

Estimating Cycle Time Percentile Curves for Manufacturing Systems via Simulation

Yang, F., Ankenman, B. E., & Nelson, B. L. (2008) · INFORMS journal on computing · doi:10.1287/ijoc.1080.0272 · Cited by 48 · see citing works

A heteroscedastic measurement error model based on skew and heavy-tailed distributions with known error variances

Tomaya, L. Y. C., & de Castro, M. (2018) · Journal of Statistical Computation and Simulation · doi:10.1080/00949655.2018.1452925 · Cited by 48 · see citing works

Inconsistency of the MDL: On the Performance of Model Order Selection Criteria With Increasing Signal-to-Noise Ratio

Ding, Q., & Kay, S. (2011) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2011.2108293 · Cited by 47 · see citing works

Semiparametric inference in a GARCH-in-mean model

Christensen, B. J., Dahl, C. M., & Iglesias, E. M. (2011) · Journal of Econometrics · doi:10.1016/j.jeconom.2011.09.028 · Cited by 46 · see citing works

Comparing the Performance of Eight Item Preknowledge Detection Statistics

Belov, D. I. (2015) · Applied Psychological Measurement · doi:10.1177/0146621615603327 · Cited by 45 · see citing works

Statistical learning and estimation of piano fingering

Nakamura, E., Saito, Y., & Yoshii, K. (2019) · Information Sciences · doi:10.1016/j.ins.2019.12.068 · Cited by 45 · see citing works

Sparse Estimation of Polynomial and Rational Dynamical Models

Rojas, C. R., Tóth, R., & Hjalmarsson, H. (2014) · IEEE Transactions on Automatic Control · doi:10.1109/tac.2014.2351711 · Cited by 44 · see citing works

Fidelity, Soundness, and Efficiency of Interleaved Comparison Methods

Hofmann, K., Whiteson, S., & de Rijke, M. (2013) · ACM Transactions on Information Systems · doi:10.1145/2536736.2536737 · Cited by 44 · see citing works

Regression with spatially misaligned data

Madsen, L. J., Ruppert, D., & Altman, N. (2007) · Environmetrics · doi:10.1002/env.888 · Cited by 44 · see citing works

Goodness-of-fit tests for mixed model diagnostics

Jiang, J. (2001) · The Annals of Statistics · doi:10.1214/aos/1013699997 · Cited by 44 · see citing works

Evaluation of P(Xt>Yt ) when both Xt and Yt are residual lifetimes of two systems

Zardasht, V., & Asadi, M. (2010) · Statistica Neerlandica · doi:10.1111/j.1467-9574.2010.00464.x · Cited by 43 · see citing works

Fisher Information in an Order Statistic and its Concomitant

Abo-Eleneen, Z. A., & Nagaraja, H. N. (2002) · Annals of the Institute of Statistical Mathematics · doi:10.1023/a:1022479514859 · Cited by 43 · see citing works

Periodontitis and Plasma C‐Reactive Protein During Pregnancy

Pitiphat, W., JOSHIPURA, K. J., Rich-Edwards, J. W., Williams, P. L., Douglass, C. W., & Gillman, M. W. (2006) · Journal of Periodontology · doi:10.1902/jop.2006.050193 · Cited by 43 · see citing works

Karl Pearson Chi-Square Test The Dawn of Statistical Inference

Rao, C. R. (2002) · Birkhäuser Boston eBooks · doi:10.1007/978-1-4612-0103-8_2 · Cited by 42 · see citing works

Distributed Online Simultaneous Fault Detection for Multiple Sensors

Rajagopal, R., Nguyen, X., Çöleri, S., & Varaiya, P. P. (2008) · ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN) · doi:10.1109/ipsn.2008.41 · Cited by 42 · see citing works

Free-Knot Polynomial Splines with Confidence Intervals

Mao, W., & Zhao, L. H. (2003) · Journal of the Royal Statistical Society Series B (Statistical Methodology) · doi:10.1046/j.1369-7412.2003.00422.x · Cited by 42 · see citing works

Pathwise Estimation of Probability Sensitivities Through Terminating or Steady-State Simulations

Hong, L. J., & Liu, G. (2009) · Operations Research · doi:10.1287/opre.1090.0739 · Cited by 41 · see citing works

Signal Amplitude Estimation and Detection From Unlabeled Binary Quantized Samples

Wang, G., Zhu, J., Blum, R. S., Willett, P., Maranò, S., Matta, V., & Braca, P. (2018) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2018.2849704 · Cited by 40 · see citing works

Decoding Movement Trajectories Through a T-Maze Using Point Process Filters Applied to Place Field Data from Rat Hippocampal Region CA1

Huang, Y., Brandon, M. P., Griffin, A. L., Hasselmo, M. E., & Eden, U. T. (2009) · Neural Computation · doi:10.1162/neco.2009.10-08-893 · Cited by 40 · see citing works

Marginal likelihood inference for a model for item responses and response times

Glas, C. A. W., & van der Linden, W. J. (2010) · British Journal of Mathematical and Statistical Psychology · doi:10.1348/000711009x481360 · Cited by 40 · see citing works

Delta Method

Cox, C. (2005) · Encyclopedia of Biostatistics · doi:10.1002/0470011815.b2a15029 · Cited by 40 · see citing works

The Bootstrap

Dasgupta, A. (2008) · Springer eBooks · doi:10.1007/978-0-387-75971-5_29 · Cited by 39 · see citing works

Skart: A skewness- and autoregression-adjusted batch-means procedure for simulation analysis

Tafazzoli, A., & Wilson, J. R. (2010) · IIE Transactions · doi:10.1080/0740817x.2010.504688 · Cited by 38 · see citing works

Measuring agreement in method comparison studies with heteroscedastic measurements

Nawarathna, L. S., & Choudhary, P. K. (2013) · Statistics in Medicine · doi:10.1002/sim.5955 · Cited by 37 · see citing works

Diagnostic checking for time series models with conditional heteroscedasticity estimated by the least absolute deviation approach

Li, G., & Li, W. K. (2005) · Biometrika · doi:10.1093/biomet/92.3.691 · Cited by 38 · see citing works

Biometrical Models in Behavioral Genetics

Neale, M. C. (2009) · Springer eBooks · doi:10.1007/978-0-387-76727-7_2 · Cited by 38 · see citing works

Monotonicity-preserving bootstrapped Kriging metamodels for expensive simulations

Kleijnen, J. P. C., & van Beers, W. C. M. (2012) · Journal of the Operational Research Society · doi:10.1057/jors.2011.148 · Cited by 37 · see citing works

Sparse estimation based on a validation criterion

Rojas, C. R., & Hjalmarsson, H. (2011) · IEEE Conference on Decision and Control (CDC) · doi:10.1109/cdc.2011.6161189 · Cited by 36 · see citing works

A Bivariate Lognormal Response-Time Model for the Detection of Collusion Between Test Takers

van der Linden, W. J. (2009) · Journal of Educational and Behavioral Statistics · doi:10.3102/1076998609332107 · Cited by 36 · see citing works

Estimating the codifference function of linear time series models with infinite variance

Rosadi, D., & Deistler, M. (2009) · Metrika · doi:10.1007/s00184-009-0285-9 · Cited by 35 · see citing works

Source Enumeration via the EEF Criterion

Xu, C., & Kay, S. (2008) · IEEE Signal Processing Letters · doi:10.1109/lsp.2008.2001112 · Cited by 35 · see citing works

Separability analysis of wetlands in Canada using multi-source SAR data

Amani, M., Salehi, B., Mahdavi, S., & Brisco, B. (2019) · GIScience & Remote Sensing · doi:10.1080/15481603.2019.1643530 · Cited by 34 · see citing works

Exposure-Referred Signal-to-Noise Ratio for Digital Image Sensors

Gnanasambandam, A., & Chan, S. H. (2022) · IEEE Transactions on Computational Imaging · doi:10.1109/tci.2022.3187657 · Cited by 34 · see citing works

Large Sample Theory

Ferguson, T. S. (1995) · Cited by 9 · see citing works

Basic Large Sample Theory

Wakefield, J. (2012) · Springer series in statistics · doi:10.1007/978-1-4419-0925-1_19

Large Sample Methods in Statistics (1994)

Sen, P. K., & Singer, J. M. (2017) · CRC Press eBooks · doi:10.1201/9780203711606 · Cited by 36 · see citing works

Large-Sample Theory of Sequential Estimation

Anscombe, F. J. (1949) · Biometrika · doi:10.2307/2332681 · Cited by 8 · see citing works

Large sample methods in statistics an introduction with applications

Sen, P. K., & Singer, J. M. (1993) · Cited by 23 · see citing works