hydroState (version 0.2.0.0)

build.all: Builds all hydroState models

Description

build.all builds all possible combinations of hydroState models. The same fields are available as in build in order to specify the type of models to be built. After all models are built, they are fitted using the same fit.hydroState() function.

Usage

build.all(
  input.data = data.frame(year = c(), flow = c(), precip = c()),
  data.transform = NULL,
  parameters = NULL,
  seasonal.parameters = NULL,
  state.shift.parameters = NULL,
  error.distribution = NULL,
  flickering = FALSE,
  transition.graph = NULL,
  summary.table = NULL,
  siteID = NULL
)

Value

A list of built hydroState models with every combination of objects ready to be fitted

Arguments

input.data

dataframe of annual, seasonal, or monthly runoff and precipitation observations. Gaps with missing data in either streamflow or precipitation are permitted, and the handling of them is further discussed in build. Monthly data is required when using seasonal.parameters that assumes selected model parameters are better defined with a sinusoidal function.

data.transform

character string of method of transformation. If empty, the default builds all possible combinations of models with boxcox data transformation.

parameters

character vector of parameters to determine model form. If empty, the default builds all possible combinations of model forms.

seasonal.parameters

character vector of parameters with sinusoidal function to represent seasonal variation. Requires monthly or seasonal data. If empty and monthly or seasonal data is given, the default builds all possible combinations of models with a seasonal parameter for each and all parameters.

state.shift.parameters

character vector of one or all parameters to identify state dependent parameters. Only one set of parameters permitted. If empty, the default builds all possible model combinations with c('a0','std') as state shift parameters.

error.distribution

character string of the distribution in the HMM error. If empty, the default builds models with all possible combinations of error distribution: c('truc.normal', 'normal','gamma')

flickering

logical TRUE/FALSE. TRUE = allows more sensitive markov flickering between states over time. When FALSE (default), state needs to persist for at least three time steps before state shift can occur.

transition.graph

matrix given the number of states. If empty, the default builds models with all possible combinations of states: 1-state matrix (1 by 1): matrix(TRUE,1,1), 2-state matrix (2 by 2): matrix(TRUE,2,2), 3-state matrix (3 by 3): matrix(TRUE,3,3).

summary.table

data frame with a table summarizing all built models and corresponding reference model. From function summary(). If empty, summary table will be built automatically.

siteID

character string of site identifier.

Details

build.all

All possible combinations of hydroState models are built for each auto-correlation lag and residual distribution from 1 to 3 states for a specified data transformation. This allows for investigation of state changes in the state.shift.parameters: the intercept c('a0', 'std') or slope c('a1', 'std'). To reduce the number of models in the search, specify which field(s) to remain constant. For example, to investigate the best model with the number of auto-correlation terms and number of states with a boxcox data transform and gamma distribution of the residuals, set data.transform to boxcox and error.distribution to gamma. If no fields are specified, all possible model combinations are built. If investigating state shifts in the intercept a0 and slope a1, it is recommended to build and fit the model combinations separately.

Examples

# Load data
data(streamflow_annual_221201)

# Build all annual models with state shift in intercept 'a0'
all.annual.models = build.all(input.data = streamflow_annual_221201,
                                    state.shift.parameters = c('a0','std'),
                                     siteID = '221201')

# OR

# Build all annual models with state shift in slope 'a1'
all.annual.models = build.all(input.data = streamflow_annual_221201,
                                    state.shift.parameters = c('a1','std'),
                                     siteID = '221201')