A function for calibrating a Geographically and Temporally Weighted Regression (GTWR) model.
gtwr(formula, data, regression.points, obs.tv, reg.tv, st.bw, kernel="bisquare",
adaptive=FALSE, p=2, theta=0, longlat=F,lamda=0.05,t.units = "auto",ksi=0,
st.dMat)A list of class “gtwrm”:
a list class object including the model fitting parameters for generating the report file
a list class object including the diagnostic information of the model fitting
an object of class inheriting from “lm”, see lm.
a SpatialPointsDataFrame (may be gridded), or SpatialPolygonsDataFrame object (see package “sp”), or sf object (see package “sf”) integrated with regression.points, GTWR coefficient estimates, y value,predicted values, coefficient standard errors and t-values in its "data" slot.
starting and ending time.
the function call used.
Regression model formula of a formula object
a Spatial*DataFrame, i.e. SpatialPointsDataFrame or SpatialPolygonsDataFrame as defined in package sp, or a sf object defined in package sf
a Spatial*DataFrame object, i.e. SpatialPointsDataFrame or SpatialPolygonsDataFrame as defined in package sp; Note that no diagnostic information will returned if it is assigned
a vector of time tags for each observation, which could be numeric or of POSIXlt class
a vector of time tags for each regression location, which could be numeric or of POSIXlt class
spatio-temporal bandwidth used in the weighting function, possibly calculated by bw.gwr;fixed (distance) or adaptive bandwidth(number of nearest neighbours)
function chosen as follows:
gaussian: wgt = exp(-.5*(vdist/bw)^2);
exponential: wgt = exp(-vdist/bw);
bisquare: wgt = (1-(vdist/bw)^2)^2 if vdist < bw, wgt=0 otherwise;
tricube: wgt = (1-(vdist/bw)^3)^3 if vdist < bw, wgt=0 otherwise;
boxcar: wgt=1 if dist < bw, wgt=0 otherwise
if TRUE calculate an adaptive kernel where the bandwidth (bw) corresponds to the number of nearest neighbours (i.e. adaptive distance); default is FALSE, where a fixed kernel is found (bandwidth is a fixed distance)
the power of the Minkowski distance, default is 2, i.e. the Euclidean distance
an angle in radians to rotate the coordinate system, default is 0
if TRUE, great circle distances will be calculated
an parameter between 0 and 1 for calculating spatio-temporal distance
character string to define time unit
an parameter between 0 and PI for calculating spatio-temporal distance, see details in Wu et al. (2014)
a pre-specified spatio-temporal distance matrix, and can be calculated via the function st.dist
Binbin Lu binbinlu@whu.edu.cn
Huang, B., Wu, B., & Barry, M. (2010). Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices. International Journal of Geographical Information Science, 24, 383-401.
Wu, B., Li, R., & Huang, B. (2014). A geographically and temporally weighted autoregressive model with application to housing prices. International Journal of Geographical Information Science, 28, 1186-1204.
Fotheringham, A. S., Crespo, R., & Yao, J. (2015). Geographical and Temporal Weighted Regression (GTWR). Geographical Analysis, 47, 431-452.