Frank Lad

1.2k citations
38 papers · 736 · h-index 12

Impact in

Papers in

Frank Lad

32 papers receiving 653 citations

Peers

Frank Lad
Comparison fields: 5 of 117
  • Statistics and Probability 232
  • Developmental Biology 50
  • General Decision Sciences 36
  • Statistics, Probability and Uncertainty 114
  • Management Science and Operations Research 83
Replace Mohan Delampady with:
Mohan Delampady India
David R. Bickel Canada
Michael Evans Canada
C. H. Kapadia United States
Robert King Australia
S. K. Katti United States
Sophie Donnet France
A. F. M. Smith United Kingdom
Bernard W. Lindgren
C. D. Litton United Kingdom
Frank Lad relative to Mohan Delampady India Mohan Delampady's profile →
Citations per field
00.5×
Mohan Delampady · 1×
Citations per year

Countries citing papers authored by Frank Lad

Since Specialization
Citations

This map shows the geographic impact of Frank Lad's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Frank Lad with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Frank Lad more than expected).

Fields of papers citing papers by Frank Lad

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Frank Lad. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Frank Lad. The network helps show where Frank Lad may publish in the future.

Co-authors

The 13 scholars most cited alongside Frank Lad, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Frank Lad Line = papers co-authored together Frank Lad links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 38 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2015205
2 199781
3 199172
4
Approximating the Distribution for Sums of Products of Normal Variables
200368
5 199263
6 198446
7 198541
8 200835
9 201814
10 199214
11 199813
12 201211
13 198410
14 19859
15 20206
16 19786
17 20066
18 20215
19 19924
20 20213

About Frank Lad

Frank Lad is a scholar working on Artificial Intelligence, Statistical and Nonlinear Physics, Management Science and Operations Research, Economics and Econometrics and Statistics and Probability, having authored 38 papers that have together received 736 indexed citations. Recurring topics across this work include Statistical Mechanics and Entropy (8 papers), Forecasting Techniques and Applications (7 papers), Bayesian Modeling and Causal Inference (7 papers), Quantum Mechanics and Applications (6 papers), Decision-Making and Behavioral Economics (4 papers), Complex Systems and Time Series Analysis (4 papers), Philosophy and History of Science (4 papers) and Market Dynamics and Volatility (3 papers). The work is most often cited by research in Statistics and Probability (232 citations), Developmental Biology (50 citations), General Decision Sciences (36 citations), Statistics, Probability and Uncertainty (114 citations) and Management Science and Operations Research (83 citations). Frank Lad has collaborated with scholars based in New Zealand, Italy and United States. Frequent co-authors include Giuseppe Sanfilippo, Gianna Agrò, Elisabeth Slooten, Tom Leonard, Robert S. Ware, Gail Blattenberger, Jon R. Miller, Steve Dawson, William F. Taylor and James Dickey. Their work appears in journals such as The American Statistician, Marine Mammal Science, Soft Computing, Journal of Statistical Computation and Simulation and Canadian Journal of Zoology.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

Explore authors with similar magnitude of impact