norm_chisq: Normalized Chi-Squared Test for Circular Data

In tectonicr: Analyzing the Orientation of Maximum Horizontal Stress

Normalized Chi-Squared Test for Circular Data

Description

A quantitative comparison between the predicted and observed directions of \sigma_{Hmax} is obtained by the calculation of the average azimuth and by a normalized \chi^2 test.

Usage

norm_chisq(obs, prd, unc)

Arguments

obs	Numeric vector containing the observed azimuth of \sigma_{Hmax}, same length as prd
prd	Numeric vector containing the modeled azimuths of \sigma_{Hmax}, i.e. the return object from model_shmax()
unc	Uncertainty of observed \sigma_{Hmax}, either a numeric vector or a number

Details

The normalized \chi^2 test is

{Norm} \chi^2_i = = \frac{ \sum^M_{i = 1} \left( \frac{\alpha_i - \alpha_{{predict}}}{\sigma_i} \right) ^2} {\sum^M_{i = 1} \left( \frac{90}{\sigma_i} \right) ^2 }

The value of the chi-squared test statistic is a number between 0 and 1 indicating the quality of the predicted \sigma_{Hmax} directions. Low values (\le 0.15) indicate good agreement, high values (> 0.7) indicate a systematic misfit between predicted and observed \sigma_{Hmax} directions.

Value

Numeric vector

References

Wdowinski, S., 1998, A theory of intraplate tectonics. Journal of Geophysical Research: Solid Earth, 103, 5037-5059, doi: 10.1029/97JB03390.

Examples

data("nuvel1")
PoR <- subset(nuvel1, nuvel1$plate.rot == "na") # North America relative to
# Pacific plate
data(san_andreas)
point <- data.frame(lat = 45, lon = 20)
prd <- model_shmax(point, PoR)
norm_chisq(obs = c(50, 40, 42), prd$sc, unc = c(10, NA, 5))

data(san_andreas)
prd2 <- PoR_shmax(san_andreas, PoR, type = "right")
norm_chisq(obs = prd2$azi.PoR, 135, unc = san_andreas$unc)

tectonicr documentation built on Sept. 11, 2024, 6:05 p.m.