hisse

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

re-building of vignette outputs

Error(s) in re-building vignettes:
--- re-building 'Clade-specific-sampling.Rmd' using rmarkdown
Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-2'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-3'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-4'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnamed-chunk-5'. Reason:
Error : The formatR package is required by the chunk option tidy = TRUE but not installed; tidy = TRUE will be ignored.

Warning in eng_r(options) :
  Failed to tidy R code in chunk 'unnam
...[truncated]...
e https://yihui.org/tinytex/r/#debugging for debugging tips. See hisse-fisse-type1-vignette.log for more info.
--- failed re-building 'hisse-fisse-type1-vignette.Rmd'

--- re-building 'hisse-new-vignette.Rmd' using rmarkdown
--- finished re-building 'hisse-new-vignette.Rmd'

--- re-building 'hisse-vignette.Rmd' using rmarkdown
! Package pdftex.def Error: File `a579c42f63b84e3004471eef3bbaa39b02ddeca8.pdf'
 not found: using draft setting.

Error: processing vignette 'hisse-vignette.Rmd' failed with diagnostics:
LaTeX failed to compile D:/RCompile/CRANpkg/local/4.4/hisse.Rcheck/vign_test/hisse/vignettes/hisse-vignette.tex. See https://yihui.org/tinytex/r/#debugging for debugging tips. See hisse-vignette.log for more info.
--- failed re-building 'hisse-vignette.Rmd'

SUMMARY: processing the following files failed:
  'GeoHiSSE-vignette.Rmd' 'MiSSE-vignette.Rmd' 'adding_fossils.Rmd'
  'hisse-fisse-type1-vignette.Rmd' 'hisse-vignette.Rmd'

Error: Vignette re-building failed.
Execution halted

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^

Rd files

checkRd: (-1) generateMiSSEGreedyCombinations.Rd:25: Lost braces
    25 | Estimating extinction rates is hard. This affects all diversification models (even if all you want and look at is speciation rate, extinction rate estimates still affect what this is as they affect the likelihood). It is most noticeable in MiSSE with eps, the extinction fraction (extinction rate divided by speciation rate). One option, following Magallon & Sanderson (2001), is to set extinction fraction at set values. By default, we use theirs, 0 (meaning a Yule model - no extinction) or 0.9 (a lot of extinction, though still less than paleontoligists find). You can set your own in \code{fixed.eps.tries}. If you only want to use fixed values, and not estimate, get rid of the NA, as well. However, don't \dQuote{cheat} -- if you use a range of values for fixed.eps, it's basically doing a search for this, though the default AICc calculation doesn't dQuote{know} this to penalize it for another parameter.
       |    
...[truncated]...
four hidden states. They can be constrained: the easiest way is to have, say, turnover having an independent rate for each hidden state and eps having the same rate for all the hidden states. If \code{vary.both} is set to FALSE, all models are of this sort: if turnover varies, eps is constant across all hidden states, or vice versa. Jeremy Beaulieu prefers this. If \code{vary.both} is set to TRUE, both can vary: for example, there could be five hidden states for both turnover and eps, but turnover lets each of these have a different rate, but eps only allows three values (so that eps_A and eps_D might be forced to be equal, and eps_B and eps_E might be forced to be equal). Brian O'Meara would consider allowing this, while cautioning you about the risks of too many parameters.
       |                                                                                                                                                                                                            ^