diff --git a/.Rbuildignore b/.Rbuildignore index 9b6ce103..65149673 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -14,3 +14,5 @@ cran-comments.md ^_pkgdown\.yml$ ^docs$ ^pkgdown$ +Clarity.txt +^vignettes \ No newline at end of file diff --git a/DESCRIPTION b/DESCRIPTION index 9cfb92b0..306d29e3 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -18,18 +18,19 @@ Description: Animal abundance estimation via conventional, multiple covariate fitting is performed via maximum likelihood. Also included are diagnostics and plotting for fitted detection functions. Abundance estimation is via a Horvitz-Thompson-like estimator. -Version: 3.0.0.9004 +Version: 3.0.0.9006 URL: https://github.com/DistanceDevelopment/mrds/ BugReports: https://github.com/DistanceDevelopment/mrds/issues Depends: - R (>= 3.0) + R (>= 4.1.0) Imports: optimx (>= 2013.8.6), mgcv, methods, numDeriv, nloptr, - Rsolnp + Rsolnp, + Rdpack Suggests: Distance, testthat, @@ -38,4 +39,5 @@ Suggests: rmarkdown, bookdown RoxygenNote: 7.3.2 +RdMacros: Rdpack Encoding: UTF-8 diff --git a/NAMESPACE b/NAMESPACE index 507a4dc3..25f8a9e3 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -72,6 +72,7 @@ import(Rsolnp) import(mgcv) import(nloptr) import(optimx) +importFrom(Rdpack,reprompt) importFrom(grDevices,dev.interactive) importFrom(grDevices,dev.new) importFrom(grDevices,devAskNewPage) diff --git a/NEWS.md b/NEWS.md index 7c632173..fdd00ccb 100644 --- a/NEWS.md +++ b/NEWS.md @@ -5,6 +5,7 @@ Bug Fixes * Fixed formatting issue in flnl.grad help * Now displays a warning if the user tries to fit a detection function with covariates using MCDS.exe which is not either a half-normal or a hazard rate model. (Issue #113) * Fixed so that the MCDS.exe does not try to fit a negative exponential in place of a gamme key function. (Issue #113) +* Now issues warnings when there is only a single transect and varflag option is 1 or 2. (Issue #115) # mrds 3.0.0 diff --git a/R/ddf.R b/R/ddf.R index 856e1084..dce55b30 100644 --- a/R/ddf.R +++ b/R/ddf.R @@ -71,7 +71,7 @@ #' for the log of the scale parameter of the key function (e.g., the equivalent #' of the standard deviation in the half-normal). The variable \code{distance} #' should not be included in the formula because the scale is for distance. -#' See Marques, F.F.C. and S.T. Buckland (2004) for more details on the +#' See \insertCite{marques2004;textual}{mrds} for more details on the #' representation of the scale formula. For the hazard rate and gamma #' functions, an additional \code{shape.formula} can be specified for the model #' of the shape parameter. The default will be ~1. @@ -91,7 +91,7 @@ #' functions are \code{formula} and \code{link}. At present, only \code{glm} #' is allowed and it is restricted to \code{link=logit}. Thus, currently the #' only form for the conditional detection functions is logistic as expressed -#' in eq 6.32 of Laake and Borchers (2004). In contrast to \code{dsmodel}, the +#' in eq 6.32 of \insertCite{laake2004;textual}{mrds}. In contrast to \code{dsmodel}, the #' argument \code{formula} will typically include \code{distance} and all other #' covariates that affect detection probability. For example, #' \code{mrmodel=~glm(formula=~distance+size+sex)} constructs a conditional @@ -209,7 +209,7 @@ #' } #' #' Examples of distance sampling analyses are available at -#' \url{https://examples.distancesampling.org/}. +#' \url{https://distancesampling.org/resources/vignettes.html}. #' #' Hints and tips on fitting (particularly optimisation issues) are on the #' \code{\link{mrds_opt}} manual page. @@ -228,15 +228,8 @@ #' \code{\link{ddf.io.fi}}, \code{\link{ddf.trial}}, #' \code{\link{ddf.trial.fi}}, \code{\link{ddf.rem}}, \code{\link{ddf.rem.fi}}, #' \code{\link{mrds_opt}} -#' @references Laake, J.L. and D.L. Borchers. 2004. Methods for incomplete -#' detection at distance zero. In: Advanced Distance Sampling, eds. S.T. -#' Buckland, D.R.Anderson, K.P. Burnham, J.L. Laake, D.L. Borchers, and L. -#' Thomas. Oxford University Press. -#' -#' Marques, F.F.C. and S.T. Buckland. 2004. Covariate models for the detection -#' function. In: Advanced Distance Sampling, eds. S.T. Buckland, -#' D.R.Anderson, K.P. Burnham, J.L. Laake, D.L. Borchers, and L. Thomas. -#' Oxford University Press. +#' @references +#' \insertAllCited{} #' @keywords ~Statistical Models #' @examples #' # load data diff --git a/R/dht.R b/R/dht.R index 89bcbd07..ada18b89 100644 --- a/R/dht.R +++ b/R/dht.R @@ -10,8 +10,7 @@ #' samples within any regional stratification. For clustered populations, #' \eqn{E(s)} and its standard error are also output. #' -#' Abundance is estimated with a Horvitz-Thompson-like estimator (Huggins 1989, -#' 1991; Borchers et al 1998; Borchers and Burnham 2004). The abundance in the +#' Abundance is estimated with a Horvitz-Thompson-like estimator (\insertCite{huggins1989;nobrackets}{mrds}; \insertCite{huggins1991;nobrackets}{mrds}; \insertCite{borchers1998;nobrackets}{mrds}; \insertCite{borchers2004;nobrackets}{mrds}). The abundance in the #' sampled region is simply \eqn{1/p_1 + 1/p_2 + ... + 1/p_n} where \eqn{p_i} #' is the estimated detection probability for the \eqn{i}th detection of #' \eqn{n} total observations. It is not strictly a Horvitz-Thompson estimator @@ -78,7 +77,7 @@ #' If the argument \code{se=TRUE}, standard errors for density and abundance is #' computed. Coefficient of variation and log-normal confidence intervals are #' constructed using a Satterthwaite approximation for degrees of freedom -#' (Buckland et al. 2001 p. 90). The function \code{\link{dht.se}} computes the +#' (\insertCite{buckland2001;nobrackets}{mrds} p 90). The function \code{\link{dht.se}} computes the #' variance and interval estimates. #' #' The variance has two components: @@ -88,7 +87,7 @@ #' \item variation in abundance due to random sample selection; #' } #' The first component (model parameter uncertainty) is computed using a delta -#' method estimate of variance (Huggins 1989, 1991, Borchers et al. 1998) in +#' method estimate of variance (\insertCite{huggins1989;nobrackets}{mrds}; \insertCite{huggins1991;nobrackets}{mrds}; \insertCite{borchers1998;nobrackets}{mrds}) in #' which the first derivatives of the abundance estimator with respect to the #' parameters in the detection function are computed numerically (see #' \code{\link{DeltaMethod}}). @@ -99,17 +98,16 @@ #' to calculate encounter rate: #' \itemize{ #' \item \code{0} uses a binomial variance for the number of observations -#' (equation 13 of Borchers et al. 1998). This estimator is only useful if the +#' (equation 13 of \insertCite{borchers1998;nobrackets}{mrds}. This estimator is only useful if the #' sampled region is the survey region and the objects are not clustered; this #' situation will not occur very often; #' \item \code{1} uses the encounter rate \eqn{n/L} (objects observed per unit -#' transect) from Buckland et al. (2001) pg 78-79 (equation 3.78) for line -#' transects (see also Fewster et al, 2009 estimator R2). This variance +#' transect) from \insertCite{buckland2001;textual}{mrds} pg 78-79 (equation 3.78) for line +#' transects (see also \insertCite{fewster2009;nobrackets}{mrds} estimator R2). This variance #' estimator is not appropriate if \code{size} or a derivative of \code{size} #' is used in the detection function; #' \item \code{2} is the default and uses the encounter rate estimator -#' \eqn{\hat{N}/L} (estimated abundance per unit transect) suggested by Innes -#' et al (2002) and Marques & Buckland (2004). +#' \eqn{\hat{N}/L} (estimated abundance per unit transect) suggested by \insertCite{innes2002;textual}{mrds} and \insertCite{marques2004;textual}{mrds} #' } #' #' In general if any covariates are used in the models, the default @@ -118,13 +116,14 @@ #' the mean group size and standard error is also reported. #' #' For options \code{1} and \code{2}, it is then possible to choose one of the -#' estimator forms given in Fewster et al (2009) for line transects: +#' estimator forms given in \insertCite{fewster2009;textual}{mrds} +#' for line transects: #' \code{"R2"}, \code{"R3"}, \code{"R4"}, \code{"S1"}, \code{"S2"}, -#' \code{"O1"}, \code{"O2"} or \code{"O3"} by specifying the \code{ervar=} -#' option (default \code{"R2"}). For points, either the \code{"P2"} or +#' \code{"O1"}, \code{"O2"} or \code{"O3"} can be used by specifying \code{ervar} +#' in the list of options provided by the \code{options} argument +#' (default \code{"R2"}). For points, either the \code{"P2"} or #' \code{"P3"} estimator can be selected (>=mrds 2.3.0 default \code{"P2"}, -#' <= mrds 2.2.9 default \code{"P3"}). See \code{\link{varn}} and Fewster -#' et al (2009) for further details on these estimators. +#' <= mrds 2.2.9 default \code{"P3"}). See \code{\link{varn}} and \insertCite{fewster2009;textual}{mrds} for further details on these estimators. #' #' @param model ddf model object #' @param region.table \code{data.frame} of region records. Two columns: @@ -187,42 +186,12 @@ #'} #' #' @author Jeff Laake, David L Miller -#' @seealso print.dht dht.se +#' @seealso \code{\link{print.dht}} \code{\link{dht.se}} #' @references -#' -#' Borchers, D.L., S.T. Buckland, P.W. Goedhart, E.D. Clarke, and S.L. Hedley. -#' 1998. Horvitz-Thompson estimators for double-platform line transect -#' surveys. Biometrics 54: 1221-1237. -#' -#' Borchers, D.L. and K.P. Burnham. General formulation for distance sampling -#' pp 10-11 In: Advanced Distance Sampling, eds. S.T. Buckland, D.R.Anderson, -#' K.P. Burnham, J.L. Laake, D.L. Borchers, and L. Thomas. Oxford University -#' Press. -#' -#' Buckland, S.T., D.R.Anderson, K.P. Burnham, J.L. Laake, D.L. Borchers, and -#' L. Thomas. 2001. Introduction to Distance Sampling: Estimating Abundance -#' of Biological Populations. Oxford University Press. -#' -#' Fewster, R.M., S.T. Buckland, K.P. Burnham, D.L. Borchers, P.E. Jupp, J.L. -#' Laake and L. Thomas. 2009. Estimating the encounter rate variance in -#' distance sampling. Biometrics 65: 225-236. -#' -#' Huggins, R.M. 1989. On the statistical analysis of capture experiments. -#' Biometrika 76:133-140. -#' -#' Huggins, R.M. 1991. Some practical aspects of a conditional likelihood -#' approach to capture experiments. Biometrics 47: 725-732. -#' -#' Innes, S., M.P. Heide-Jorgensen, J.L. Laake, K.L. Laidre, H.J. Cleator, P. -#' Richard, and R.E.A. Stewart. 2002. Surveys of belugas and narwhals in the -#' Canadian High Arctic in 1996. NAMMCO Scientific Publications 4: 169-190. -#' -#' Marques, F.F.C. and S.T. Buckland. 2004. Covariate models for the detection -#' function. In: Advanced Distance Sampling, eds. S.T. Buckland, -#' D.R.Anderson, K.P. Burnham, J.L. Laake, D.L. Borchers, and L. Thomas. -#' Oxford University Press. +#' \insertAllCited{} #' @keywords utility #' @importFrom stats aggregate +#' @importFrom Rdpack reprompt #' @export dht <- function(model, region.table, sample.table, obs.table=NULL, subset=NULL, se=TRUE, options=list()){ @@ -626,6 +595,28 @@ dht <- function(model, region.table, sample.table, obs.table=NULL, subset=NULL, } result <- list(individuals=individuals) } + + # Check to see if need to issue user with a warning if there were any strata with only one sample. + if(any(result$individuals$summary$k == 1)){ + # if there is only one strata + if(nrow(result$individuals$summary) == 1){ + if(options$varflag == 1){ + warning("Only one sample, assuming variance of n is Poisson. See help on dht.se for recommendations.", immediate. = TRUE, call. = FALSE) + }else if(options$varflag == 2){ + warning("Only one sample, assuming abundance in the covered region is Poisson. See help on dht.se for recommendations.", immediate. = TRUE, call. = FALSE) + } + }else{ + # if there are multiple strata + # find which strata have only one sample + strat.names <- result$individuals$summary$Region[result$individuals$summary$k == 1] + strat.txt <- ifelse(length(strat.names) > 1, ". For these strata, ", ". For this stratum, ") + if(options$varflag == 1){ + warning(paste("Only one sample in the following strata: ", paste(strat.names, collapse = ", "), strat.txt, "it is assumed variance of n is Poisson. See help on dht.se.", sep = ""), immediate. = TRUE, call. = FALSE) + }else if(options$varflag == 2){ + warning("Only one sample in the following strata: ", paste(strat.names, collapse = ", "), strat.txt, "it is assumed abundance in the covered region is Poisson. See help on dht.se.", immediate. = TRUE, call. = FALSE) + } + } + } # add some meta data # save enounter rate variance information diff --git a/R/dht.se.R b/R/dht.se.R index d467e2a7..819830ee 100644 --- a/R/dht.se.R +++ b/R/dht.se.R @@ -12,7 +12,7 @@ #' \item variation in abundance due to random sample selection; #' } #' The first component (model parameter uncertainty) is computed using a delta -#' method estimate of variance (Huggins 1989, 1991, Borchers et al. 1998) in +#' method estimate of variance (\insertCite{huggins1989;nobrackets}{mrds}; \insertCite{huggins1991;nobrackets}{mrds}; \insertCite{borchers1998;nobrackets}{mrds}) in #' which the first derivatives of the abundance estimator with respect to the #' parameters in the detection function are computed numerically (see #' \code{\link{DeltaMethod}}). @@ -22,18 +22,19 @@ #' estimator used. To begin with there three possible values for \code{varflag} #' to calculate encounter rate: #' \itemize{ -#' \item \code{0} uses a binomial variance for the number of observations -#' (equation 13 of Borchers et al. 1998). This estimator is only useful if the -#' sampled region is the survey region and the objects are not clustered; this -#' situation will not occur very often; +#' \item \code{0} uses a negative binomial variance for the number of +#' observations (equation 13 of \insertCite{borchers1998;nobrackets}{mrds}). +#' This estimator is only +#' useful if the sampled region is the survey region and the objects are not +#' clustered; this situation will not occur very often; #' \item \code{1} uses the encounter rate \eqn{n/L} (objects observed per unit -#' transect) from Buckland et al. (2001) pg 78-79 (equation 3.78) for line -#' transects (see also Fewster et al, 2009 estimator R2). This variance +#' transect) from \insertCite{buckland2001;textual}{mrds} pg 78-79 (equation 3.78) for line +#' transects (see also \insertCite{fewster2009;nobrackets}{mrds} estimator R2). This variance #' estimator is not appropriate if \code{size} or a derivative of \code{size} #' is used in the detection function; #' \item \code{2} is the default and uses the encounter rate estimator -#' \eqn{\hat{N}/L} (estimated abundance per unit transect) suggested by Innes -#' et al (2002) and Marques & Buckland (2004). +#' \eqn{\hat{N}/L} (estimated abundance per unit transect) suggested by +#' \insertCite{innes2002;textual}{mrds} and \insertCite{marques2004;textual}{mrds} #' } #' #' In general if any covariates are used in the models, the default @@ -42,21 +43,25 @@ #' the mean group size and standard error is also reported. #' #' For options \code{1} and \code{2}, it is then possible to choose one of the -#' estimator forms given in Fewster et al (2009). For line transects: +#' estimator forms given in \insertCite{fewster2009;textual}{mrds}. For line transects: #' \code{"R2"}, \code{"R3"}, \code{"R4"}, \code{"S1"}, \code{"S2"}, -#' \code{"O1"}, \code{"O2"} or \code{"O3"} can be used by specifying the -#' \code{ervar=} option (default \code{"R2"}). For points, either the +#' \code{"O1"}, \code{"O2"} or \code{"O3"} can be used by specifying \code{ervar} +#' in the list of options provided by the \code{options} argument +#' (default \code{"R2"}). For points, either the #' \code{"P2"} or \code{"P3"} estimator can be selected (>=mrds 2.3.0 #' default \code{"P2"}, <= mrds 2.2.9 default \code{"P3"}). See -#' \code{\link{varn}} and Fewster et al (2009) for further details -#' on these estimators. +#' \code{\link{varn}} and \insertCite{fewster2009;textual}{mrds} +#' for further details on these estimators. #' #' Exceptions to the above occur if there is only one sample in a stratum. In -#' that case it uses Poisson assumption (\eqn{Var(x)=x}) and it assumes a known -#' variance so \eqn{z=1.96} is used for critical value. In all other cases the -#' degrees of freedom for the \eqn{t}-distribution assumed for the +#' this situation, \code{varflag=0} continues to use a negative binomial +#' variance while the other options assume a Poisson variance (\eqn{Var(x)=x}), +#' where when \code{varflag=1} x is number of detections in the covered region and +#' when \code{varflag=2} x is the abundance in the covered region. It also assumes +#' a known variance so \eqn{z=1.96} is used for critical value. In all other cases +#' the degrees of freedom for the \eqn{t}-distribution assumed for the #' log(abundance) or log(density) is based on the Satterthwaite approximation -#' (Buckland et al. 2001 pg 90) for the degrees of freedom (df). The df are +#' (\insertCite{buckland2001;nobrackets}{mrds} pg 90) for the degrees of freedom (df). The df are #' weighted by the squared cv in combining the two sources of variation because #' of the assumed log-normal distribution because the components are #' multiplicative. For combining df for the sampling variance across regions @@ -84,9 +89,11 @@ #' their own code. #' @author Jeff Laake #' @seealso \code{\link{dht}}, \code{\link{print.dht}} -#' @references see \code{\link{dht}} +#' @references +#' \insertAllCited{} #' @keywords utility #' @importFrom stats qnorm qt var +#' @importFrom Rdpack reprompt dht.se <- function(model, region.table, samples, obs, options, numRegions, estimate.table, Nhat.by.sample){ # Functions Used: DeltaMethod, dht.deriv (in DeltaMethod), varn @@ -127,8 +134,9 @@ dht.se <- function(model, region.table, samples, obs, options, numRegions, # Next compute the component due to sampling of both lines and of the # detection process itself # There are 3 different options here: - # 1) varflag=0; Binomial variance of detection process - only applicable if - # survey region=covered region although it will scale up but it would be + # 1) varflag=0; Negative binomial variance of detection process - only + # applicable if survey region=covered region although it will scale up + # but it would be # a poor estimator # 2) varflag=1; delta method, with varn based on Fewster et al (2009) # estimator R2 (var(n/L)) @@ -228,10 +236,14 @@ dht.se <- function(model, region.table, samples, obs, options, numRegions, if (options$group) vars <- 0 + # if there is only one sample assume Poisson variance if(length(stratum.data$Effort.y) == 1){ if (options$varflag == 1){ + # Assuming variance of n is Poisson: var(x) = x vc2[i] <- Ni^2 * 1/stratum.data$n }else{ + # varflag = 2 + # Assuming abundance in covered region is Poisson: var(x) = x vc2[i] <- Ni^2 * 1/Ni } }else if (options$varflag == 1){ diff --git a/R/mcds_tools.R b/R/mcds_tools.R index 628783af..2290161b 100644 --- a/R/mcds_tools.R +++ b/R/mcds_tools.R @@ -19,7 +19,7 @@ #' choose to use only the R-based algorithm by setting \code{control=list(optimizer='R')}. #' #' For more information and examples comparing the R-based and `MCDS.exe` algorithms, -#' see our examples pages at https://examples.distancesampling.org/ +#' see our examples pages at https://distancesampling.org/resources/vignettes.html #' #' If you are running a non-Windows operating system, you can follow the #' instructions below to have `MCDS.exe` run using `wine`. diff --git a/R/mrds-package.R b/R/mrds-package.R index a27237d2..2c50fc02 100644 --- a/R/mrds-package.R +++ b/R/mrds-package.R @@ -1,20 +1,14 @@ #' Mark-Recapture Distance Sampling (mrds) #' -#' This package implements mark-recapture distance sampling -#' methods as described in D.L. Borchers, W. Zucchini and Fewster, -#' R.M. (1988), "Mark-recapture models for line transect surveys", -#' Biometrics 54: 1207-1220. and Laake, J.L. (1999) "Distance sampling -#' with independent observers: Reducing bias from heterogeneity by -#' weakening the conditional independence assumption." in Amstrup, -#' G.W., Garner, S.C., Laake, J.L., Manly, B.F.J., McDonald, L.L. and -#' Robertson, D.G. (eds) "Marine mammal survey and assessment -#' methods", Balkema, Rotterdam: 137-148 and Borchers, D.L., Laake, -#' J.L., Southwell, C. and Paxton, C.L.G. "Accommodating unmodelled -#' heterogeneity in double-observer distance sampling surveys". 2006. -#' Biometrics 62:372-378.) +#' This package implements both conventional distance sampling +#' analysis and mark-recapture distance sampling methods for when +#' detection on the transect is not certain. Mark-recapture distance sampling methods are described in +#' \insertCite{borchers1988;textual}{mrds}, \insertCite{laake1999;textual}{mrds} +#' and \insertCite{borchers2006;textual}{mrds} +#' #' #' Examples of distance sampling analyses are available at -#' \url{http://examples.distancesampling.org/}. +#' \url{https://distancesampling.org/resources/vignettes.html}. #' #' For help with distance sampling and this package, there is a Google Group #' \url{https://groups.google.com/forum/#!forum/distance-sampling}. @@ -27,6 +21,9 @@ #' David L. Miller , #' Jon Bishop , #' Felix Petersma +#' @importFrom Rdpack reprompt +#' @references +#' \insertAllCited{} #' @keywords package #' "_PACKAGE" #' diff --git a/R/varn.R b/R/varn.R index ce87eb79..330c80f4 100644 --- a/R/varn.R +++ b/R/varn.R @@ -4,7 +4,7 @@ #' encounter rate for a set of sample measurements (e.g., line lengths) and #' number of observations per sample. #' -#' The choice of type follows the notation of Fewster et al. (2009) in that there are 8 choices of encounter rate variance that can be computed for lines and one for points: +#' The choice of type follows the notation of \insertCite{fewster2009;textual}{mrds} in that there are 8 choices of encounter rate variance that can be computed for lines and one for points: #' #' \describe{ #' \item{\code{R2}}{random line placement with unequal line lengths @@ -30,9 +30,9 @@ #' visits per point, model-based estimator} #' } #' -#' Default value is \code{"R2"}, shown in Fewster et al. (2009) to have good +#' Default value is \code{"R2"}, shown in \insertCite{fewster2009;textual}{mrds} to have good #' performance for completely random designs for lines. For systematic parallel -#' line transect designs, Fewster et al. recommend \code{"O2"}. For point +#' line transect designs, \insertCite{fewster2009;textual}{mrds} recommend \code{"O2"}. For point #' transects the default is \code{"P2"} (but \code{"P3"} is also available). #' #' For the systematic estimators, pairs are assigned in the order they are @@ -49,13 +49,12 @@ #' @param type choice of variance estimator to use for encounter rate #' @return Variance of encounter rate as defined by arguments #' @note This function is also used with different calling arguments to compute -#' Innes et al variance of the estimated abundances/length rather than +#' \insertCite{innes2002;textual}{mrds} variance of the estimated abundances/length rather than #' observation encounter rate. The function covn is probably only valid for R3 #' and R2. Currently, the R2 form is used for all types other than R3. #' @author Jeff Laake, David L Miller -#' @references Fewster, R.M., S.T. Buckland, K.P. Burnham, D.L. Borchers, P.E. -#' Jupp, J.L. Laake and L. Thomas. 2009. Estimating the encounter rate -#' variance in distance sampling. Biometrics 65: 225-236. +#' @references +#' \insertAllCited{} #' @keywords utility #' @export varn <- function(lvec, nvec, type){ diff --git a/_pkgdown.yml b/_pkgdown.yml index 5e0319c6..ca8c9e67 100644 --- a/_pkgdown.yml +++ b/_pkgdown.yml @@ -1,6 +1,7 @@ url: ~ template: bootstrap: 5 + math-rendering: mathjax bslib: bg: "#fcfaf2" fg: "#14059e" @@ -15,12 +16,7 @@ reference: navbar: bg: primary structure: - right: [twitter, github] - components: - twitter: - icon: fa-twitter - href: https://twitter.com/distancesamp - aria-label: Twitter + right: [github] left: - text: Function reference href: reference/index.html diff --git a/docs/404.html b/docs/404.html index eea0e2c6..ea4b0fee 100644 --- a/docs/404.html +++ b/docs/404.html @@ -6,9 +6,15 @@ Page not found (404) • mrds - + - + @@ -22,7 +28,7 @@ mrds - 3.0.0 + 3.0.0.9006