Functional Autoregressive Models is a class of statistical models in functional time series analysis that extend classical autoregressive processes to infinite-dimensional spaces by modeling the current functional observation as a linear combination of past observations through a bounded linear operator.
66
Publications
5K
Citations
121
Authors
94
Institutions
Publications per year
2017–2026
17
Variants
Far Models
Publications
66
Functional Data Analysis. Springer Series in Statistics
J. O. Ramsay, B.W. Silvermann · Biometrical Journal · 1998 · 387 citations
1–5 of 66
Authors
121
- IS
5
h-index
- PK
5
h-index
- SA
4
h-index
- LH
4
h-index
- MR
3
h-index
1–5 of 121
Institutions
94
University of Chicago
Chicago, United States
5 h-index
5 publications
608 citations
Quaid-i-Azam University
Islamabad, Pakistan
5 h-index
13 publications
632 citations
University of Utah
Salt Lake City, United States
4 h-index
8 publications
439 citations
Texas A&M University
College Station, United States
4 h-index
5 publications
1K citations
National University of Singapore
Singapore, Singapore
4 h-index
6 publications
215 citations
University of North Carolina at Charlotte
Charlotte, United States
3 h-index
3 publications
855 citations
Utah State University
Logan, United States
3 h-index
5 publications
259 citations
University of Hong Kong
Pok Fu Lam, Hong Kong
2 h-index
4 publications
488 citations
1–8 of 94
Venues
- Journal of the American Statistical Association
8 publications · 1.9K citations
8
h-index
- Journal of Econometrics
5 publications · 340 citations
5
h-index
- Journal of Time Series Analysis
5 publications · 164 citations
5
h-index
- Journal of Multivariate Analysis
4 publications · 273 citations
4
h-index
- Journal of Business and Economic Statistics
JBES · 3 publications · 122 citations
3
h-index
1–5