Description Usage Arguments Details Value References See Also Examples

View source: R/nwos_mean_apply.R

This function calculates means for NWOS replicates. This is typically used with an apply function.

1 | ```
nwos_proportion_apply(r, index.rep, data, weight.rep, owner.area.name = "OWNER", domain.name, base.name = "FFO", variable.name = "FFO")
``` |

`r` |
vector of replicates numbers. |

`index.rep` |
list of observations (i.e., replicates) to include. |

`index` |
vector used to identify the location of values in the other vectors (e.g., row names). |

`weight` |
list of weights for each observation in each replicate. |

`area` |
vector of the area (of forestland) for each observation. Default = 1. |

`domain` |
vector with 1 indicating inclusion in the domain and 0 otherwise. Default = 1. |

`variable` |
vector of variable of interest. |

This function needs to be run by stratum (e.g., family forest ownerships in a state). Due to indexing (to allow for apply function), there are fewer defauly values than nwos_mean.

Mean of variable of interest. @keywords nwos

Butler, B.J. In review. Weighting for the US Forest Service, National Woodland Owner Survey. U.S. Department of Agriculture, Forest Service, Northern Research Station. Newotwn Square, PA.

nwos_mean

1 2 3 4 5 6 7 8 9 10 11 12 13 | ```
wi <- tbl_df(read.csv("data/wi.csv")) %>% mutate(ROW_NAME = row.names(wi), AC_WOOD = ACRES_FOREST, FFO = if_else(LAND_USE == 1 & OWN_CD == 45 & AC_WOOD >= 1, 1, 0), RESPONSE = if_else(RESPONSE_PROPENSITY >= 0.5, 1, 0), RESPONSE = if_else(is.na(RESPONSE_PROPENSITY), 0, RESPONSE))
WI_REPLICATES <- nwos_replicates(index = row.names(wi), point.count = wi$POINT_COUNT, R = 100)
WI_FFO_AREA_REP <- sapply(WI_REPLICATES, nwos_stratum_area_apply, index = wi$ROW_NAME, stratum = wi$FFO, state.area = 33898733)
WI_FFO_RR_REP <- sapply(WI_REPLICATES, nwos_response_rate_apply, index = wi$ROW_NAME, stratum = wi$FFO, response = wi$RESPONSE)
WI_FFO_WEIGHTS_REP <- lapply(1:length(WI_REPLICATES), nwos_weights_apply,index.rep = WI_REPLICATES, index = wi$ROW_NAME, stratum = wi$FFO, response = wi$RESPONSE, area = wi$AC_WOOD,stratum.area = WI_FFO_AREA_REP, response.rate = WI_FFO_RR_REP)
WI_FFO_OWN_AC_MEAN <- nwos_mean(weight = wi$WEIGHT, variable = wi$AC_WOOD)
WI_FFO_OWN_AC_MEAN_REP <- sapply(1:length(WI_REPLICATES), nwos_mean_apply, index.rep = WI_REPLICATES, index = wi$ROW_NAME, weight = WI_FFO_WEIGHTS_REP, variable = wi$AC_WOOD)
WI_FFO_OWN_AC_MEAN
sqrt(var(WI_FFO_OWN_AC_MEAN_REP))
WI_FFO_AC_AC_MEAN <- nwos_mean(weight = wi$WEIGHT, area = wi$AC_WOOD, variable = wi$AC_WOOD)
WI_FFO_AC_AC_MEAN_REP <- sapply(1:length(WI_REPLICATES), nwos_mean_apply, index.rep = WI_REPLICATES, index = wi$ROW_NAME, weight = WI_FFO_WEIGHTS_REP, area = wi$AC_WOOD, variable = wi$AC_WOOD)
WI_FFO_AC_AC_MEAN
sqrt(var(WI_FFO_AC_AC_MEAN_REP))
``` |

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