Details
| Original language | English |
|---|---|
| Pages (from-to) | 4547-4558 |
| Number of pages | 12 |
| Journal | Communications in Statistics - Simulation and Computation |
| Volume | 46 |
| Issue number | 6 |
| Publication status | Published - 25 Jan 2017 |
| Externally published | Yes |
Abstract
In applications of spatial statistics, it is necessary to compute the product of some matrix W of spatial weights and a vector y of observations. The weighting matrix often needs to be adapted to the specific problems, such that the computation of Wy cannot necessarily be done with available R-packages. Hence, this article suggests one possibility treating such issues. The proposed technique avoids the computation of the matrix product by calculating each entry of Wy separately. Initially, a specific spatial autoregressive process is introduced. The performance of the proposed program is briefly compared to a basic program using the matrix multiplication.
Keywords
- Curse of dimensionality, Efficient simulation in R, Spatial autoregressive model
ASJC Scopus subject areas
- Mathematics(all)
- Statistics and Probability
- Mathematics(all)
- Modelling and Simulation
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In: Communications in Statistics - Simulation and Computation, Vol. 46, No. 6, 25.01.2017, p. 4547-4558.
Research output: Contribution to journal › Article › Research › peer review
}
TY - JOUR
T1 - A note on efficient simulation of multidimensional spatial autoregressive processes
AU - Otto, Philipp
N1 - Publisher Copyright: © 2017 Taylor & Francis Group, LLC.
PY - 2017/1/25
Y1 - 2017/1/25
N2 - In applications of spatial statistics, it is necessary to compute the product of some matrix W of spatial weights and a vector y of observations. The weighting matrix often needs to be adapted to the specific problems, such that the computation of Wy cannot necessarily be done with available R-packages. Hence, this article suggests one possibility treating such issues. The proposed technique avoids the computation of the matrix product by calculating each entry of Wy separately. Initially, a specific spatial autoregressive process is introduced. The performance of the proposed program is briefly compared to a basic program using the matrix multiplication.
AB - In applications of spatial statistics, it is necessary to compute the product of some matrix W of spatial weights and a vector y of observations. The weighting matrix often needs to be adapted to the specific problems, such that the computation of Wy cannot necessarily be done with available R-packages. Hence, this article suggests one possibility treating such issues. The proposed technique avoids the computation of the matrix product by calculating each entry of Wy separately. Initially, a specific spatial autoregressive process is introduced. The performance of the proposed program is briefly compared to a basic program using the matrix multiplication.
KW - Curse of dimensionality
KW - Efficient simulation in R
KW - Spatial autoregressive model
UR - http://www.scopus.com/inward/record.url?scp=85010635724&partnerID=8YFLogxK
U2 - 10.1080/03610918.2015.1122050
DO - 10.1080/03610918.2015.1122050
M3 - Article
VL - 46
SP - 4547
EP - 4558
JO - Communications in Statistics - Simulation and Computation
JF - Communications in Statistics - Simulation and Computation
SN - 1532-4141
IS - 6
ER -