Function for optimal parameters-based geographical detector(OPGD) model.
Usage
opgd(
formula,
data,
discvar = NULL,
discnum = 3:8,
discmethod = c("sd", "equal", "geometric", "quantile", "natural"),
cores = 1,
type = "factor",
alpha = 0.95,
...
)
Arguments
- formula
A formula of OPGD model.
- data
A
data.frame
,tibble
orsf
object of observation data.- discvar
Name of continuous variable columns that need to be discretized. Noted that when
formula
hasdiscvar
,data
must have these columns. By default, all independent variables are used asdiscvar
.- discnum
(optional) A vector of number of classes for discretization. Default is
3:8
.- discmethod
(optional) A vector of methods for discretization, default is using
c("sd","equal","geometric","quantile","natural")
by invokingsdsfun
.- cores
(optional) Positive integer (default is 1). When cores are greater than 1, use multi-core parallel computing.
- type
(optional) The type of geographical detector, which must be
factor
(default),interaction
,risk
,ecological
. You can run one or more types at one time.- alpha
(optional) Specifies the size of confidence level. Default is
0.95
.- ...
(optional) Other arguments passed to
gd_bestunidisc()
. A useful parameter isseed
, which is used to set the random number seed.
Value
A list.
opt_param
optimal discretization parameter
factor
the result of factor detector
interaction
the result of interaction detector
risk
the result of risk detector
ecological
the result of ecological detector
References
Song, Y., Wang, J., Ge, Y. & Xu, C. (2020) An optimal parameters-based geographical detector model enhances geographic characteristics of explanatory variables for spatial heterogeneity analysis: Cases with different types of spatial data, GIScience & Remote Sensing, 57(5), 593-610. doi: 10.1080/15481603.2020.1760434.
Author
Wenbo Lv lyu.geosocial@gmail.com
Examples
data('sim')
opgd(y ~ xa + xb + xc, data = sim,
discvar = paste0('x',letters[1:3]),
discnum = 3:6)
#> *** Optimal Parameters-based Geographical Detector
#> Factor Detector
#>
#> | variable | Q-statistic | P-value |
#> |:--------:|:-----------:|:-----------:|
#> | xc | 0.6225785 | 5.72000e-10 |
#> | xb | 0.4800064 | 1.00905e-07 |
#> | xa | 0.3267163 | 7.64250e-05 |
#>