| ssn_params | R Documentation | 
Create a covariance parameter object for us with other functions.
See spmodel::randcov_params() for documentation regarding
random effect covariance parameter objects.
tailup_params(tailup_type, de, range)
taildown_params(taildown_type, de, range)
euclid_params(euclid_type, de, range, rotate, scale)
nugget_params(nugget_type, nugget)
| tailup_type | The tailup covariance function type. Available options
include  | 
| de | The spatially dependent (correlated) random error variance. Commonly referred to as a partial sill. | 
| range | The correlation parameter. | 
| taildown_type | The taildown covariance function type. Available options
include  | 
| euclid_type | The euclidean covariance function type. Available options
include  | 
| rotate | Anisotropy rotation parameter (from 0 to  | 
| scale | Anisotropy scale parameter (from 0 to 1) for the euclidean portion of the covariance. A value of 1 (the default) implies no scaling. | 
| nugget_type | The nugget covariance function type. Available options
include  | 
| nugget | The spatially independent (not correlated) random error variance. Commonly referred to as a nugget. | 
A parameter object with class that matches the relevant type argument.
Peterson, E.E. and Ver Hoef, J.M. (2010) A mixed-model moving-average approach to geostatistical modeling in stream networks. Ecology 91(3), 644–651.
Ver Hoef, J.M. and Peterson, E.E. (2010) A moving average approach for spatial statistical models of stream networks (with discussion). Journal of the American Statistical Association 105, 6–18. DOI: 10.1198/jasa.2009.ap08248. Rejoinder pgs. 22–24.
tailup_params("exponential", de = 1, range = 20)
taildown_params("exponential", de = 1, range = 20)
euclid_params("exponential", de = 1, range = 20, rotate = 0, scale = 1)
nugget_params("nugget", nugget = 1)
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