docs update

 ... ... @@ -13,9 +13,7 @@ analyzes its variance with the bootstrap method. The \code{data} and 13 13  the number of trees \code{K} have to be specified.  14 14  }  15 15  \usage{  16 -bootstrap(data, K, no.start.sol = 100, eps = 0, weighing = FALSE,  17 - equal.edgeweights = TRUE, seed = (-1), B = 1000,  18 - conf.interval = 0.05)  16 +bootstrap(data, K, \dots)  19 17  }  20 18   21 19  \arguments{  ... ... @@ -23,24 +21,26 @@ bootstrap(data, K, no.start.sol = 100, eps = 0, weighing = FALSE, 23 21  learning the trees mixture model. }  24 22  \item{K}{An \code{integer} larger than 0 specifying the number of  25 23  branchings in the mixture model.}  26 - \item{no.start.sol}{An \code{integer} larger than 0 specifying the number of starting solutions for the k-means  27 - algorithm. The default value is 100.}  28 - \item{eps}{A \code{numeric} giving the minimum conditional probability to include edge. The  29 - default value is 0.}  30 - \item{weighing}{A \code{logical} specifying whether to use special  31 - weights log(Pr(v)) for the edges (root, v). The default value is \code{FALSE}.}  32 - \item{equal.edgeweights}{A \code{logical} specifying whether to use  24 + \item{\dots}{  25 + \code{no.start.sol} is an \code{integer} larger than 0 specifying the number of starting solutions for the k-means  26 + algorithm. The default value is 100.  27 + \code{eps} is a \code{numeric} giving the minimum conditional probability to include edge. The  28 + default value is 0.  29 + \code{weighing} is a \code{logical} specifying whether to use special  30 + weights log(Pr(v)) for the edges (root, v). The default value is \code{FALSE}.  31 + \code{equal.edgeweights} is a \code{logical} specifying whether to use  33 32  equal edge weights in the noise component. The default value is  34 33  \code{TRUE}. When you have few data samples always use its default value  35 34  (\code{TRUE}) to ensure nonzero probabilities for all possible  36 - patterns (sets of events).}  37 - \item{seed}{A positive \code{integer} specifying the random generator  35 + patterns (sets of events).  36 + \code{seed} is a positive \code{integer} specifying the random generator  38 37  seed. The default value is (-1) and then the time is used as a  39 - random generator.}  40 - \item{B}{An \code{integer} larger than 0 specifying the number of  41 - bootstrap samples. Its default value is 1000.}  42 - \item{conf.interval}{A \code{numeric} specifying the Confidence level  43 - for the intervals. Its default value is 0.05.}  38 + random generator.  39 + \code{B} is an \code{integer} larger than 0 specifying the number of  40 + bootstrap samples. Its default value is 1000.  41 + \code{conf.interval} is a \code{numeric} specifying the Confidence level  42 + for the intervals. Its default value is 0.05.  43 + }  44 44  }  45 45   46 46  \value{ 
 ... ... @@ -18,8 +18,7 @@ 18 18  }  19 19   20 20  \usage{  21 -confIntGPS(data, K, sampling.mode = "exponential", sampling.param = 1,  22 - no.sim = 10000, B = 1000, equal.star = TRUE)  21 +confIntGPS(data, K, \dots)  23 22  }  24 23   25 24  \arguments{  ... ... @@ -29,23 +28,25 @@ confIntGPS(data, K, sampling.mode = "exponential", sampling.param = 1, 29 28  of genetic events should NOT be greater than 20.}  30 29  \item{K}{An \code{integer} larger than 0 specifying the number of  31 30  branchings in the mixture model.}  32 - \item{sampling.mode}{A \code{character} that specifies the  31 + \item{...}{  32 + \code{sampling.mode} is a \code{character} that specifies the  33 33  sampling mode ("constant" or "exponential") used in the waiting time  34 - simulations. Its default value is "exponential".}  35 - \item{sampling.param}{A \code{numeric} that specifies the  34 + simulations. Its default value is "exponential".  35 + \code{sampling.param} is a \code{numeric} that specifies the  36 36  sampling parameter corresponding to the sampling mode given by  37 - \code{sampling.mode}. Its default value is 1.}  38 - \item{no.sim}{An \code{integer} larger than 0 giving the number of  37 + \code{sampling.mode}. Its default value is 1.  38 + \code{no.sim} is an \code{integer} larger than 0 giving the number of  39 39  iterations for the waiting time simulation. Its default values is  40 - 10000.}  41 - \item{B}{An \code{integer} larger than 0 specifying the number of  40 + 10000.  41 + \code{B} is an \code{integer} larger than 0 specifying the number of  42 42  bootstrap samples used in the bootstrap analysis. Its default value  43 - is 1000.}  44 - \item{equal.star}{A \code{logical} specifying whether to use  43 + is 1000.  44 + \code{equal.star} is a \code{logical} specifying whether to use  45 45  equal edge weights in the noise component. The default value is  46 46  \code{TRUE}. When you have few data samples always use its default value  47 47  (\code{TRUE}) to ensure nonzero probabilities for all possible  48 - patterns (sets of events).}  48 + patterns (sets of events).  49 + }  49 50  }  50 51   51 52  \value{  ... ... @@ -63,7 +64,7 @@ confIntGPS(data, K, sampling.mode = "exponential", sampling.param = 1, 63 64  confidence intervals are to be calculated should not have more  64 65  than 20 genetic events. The reason for this is that the number of all possible patterns  65 66  for which the GPS values are calculated during a computationally intensive simulations  66 - is in this case $2^{20}$. This demands too much memory.  67 + is in this case $2^20$. This demands too much memory.  67 68  The GPS examples are time consuming. They are commented out because of the time restrictions of the check of the package.  68 69  For trying out the code please copy it and uncomment it.  69 70  } 
 ... ... @@ -19,12 +19,7 @@ 19 19  events in the \code{model} cannot exceed 30. 20 20  } 21 21  \usage{ 22 -distribution(model, ...) 23 - 24 -\method{distribution}{model}(model) 25 - 26 -\method{distribution}{model, sampling.mode, sampling.param, output.param}(model,  27 - sampling.mode, sampling.param, output.param) 22 +distribution(model, sampling.mode, sampling.param, output.param) 28 23  } 29 24  \arguments{ 30 25  \item{model}{An \code{RtreemixModel} object that encodes a ... ... @@ -37,7 +32,7 @@ distribution(model, ...) 37 32  corresponding to the sampling mode given by \code{sampling.mode}.} 38 33  \item{output.param}{A \code{numeric} that specifies the 39 34  sampling parameter for the observed output probabilities 40 - corresponding to the sampling mode given by \code{sampling.mode}.}  35 + corresponding to the sampling mode given by \code{sampling.mode}.}  41 36  } 42 37   43 38  \value{
 ... ... @@ -24,8 +24,7 @@ 24 24  } 25 25   26 26  \usage{ 27 -fit(data, K, no.start.sol = 100, eps = 0.01, weighing = FALSE,  28 - equal.edgeweights = TRUE, seed = (-1), noise = TRUE) 27 +fit(data, K, \dots) 29 28  } 30 29   31 30  \arguments{ ... ... @@ -33,23 +32,25 @@ fit(data, K, no.start.sol = 100, eps = 0.01, weighing = FALSE, 33 32  learning the trees mixture model.} 34 33  \item{K}{An \code{integer} larger than 0 specifying the number of 35 34  branchings in the mixture model.} 36 - \item{no.start.sol}{An \code{integer} larger than 0 specifying the number of starting solutions for the k-means 37 - algorithm. The default value is 100.} 38 - \item{eps}{A \code{numeric} giving the minimum conditional probability to include edge. The 39 - default value is 0.01.} 40 - \item{weighing}{A \code{logical} specifying whether to use special 41 - weights log(Pr(v)) for the edges (root, v). The default value is \code{FALSE}.} 42 - \item{equal.edgeweights}{A \code{logical} specifying whether to use 35 + \item{\dots}{ 36 + \code{no.start.sol} is an \code{integer} larger than 0 specifying the number of starting solutions for the k-means 37 + algorithm. The default value is 100. 38 + \code{eps} is a \code{numeric} giving the minimum conditional probability to include edge. The 39 + default value is 0.01. 40 + \code{weighing} is a \code{logical} specifying whether to use special 41 + weights log(Pr(v)) for the edges (root, v). The default value is \code{FALSE}. 42 + \code{equal.edgeweights} is a \code{logical} specifying whether to use 43 43  equal edge weights in the noise component. The default value is 44 44  \code{TRUE}. When you have few data samples always use its default value (\code{TRUE})  45 - to ensure nonzero probabilities for all possible patterns (sets of events).} 46 - \item{seed}{A positive \code{integer} specifying the random generator 45 + to ensure nonzero probabilities for all possible patterns (sets of events). 46 + \code{seed} is a positive \code{integer} specifying the random generator 47 47  seed. The default value is (-1) and then the time is used as a 48 - random generator.} 49 - \item{noise}{A \code{logical} indicating the presence of a noise 48 + random generator. 49 + \code{noise} is a \code{logical} indicating the presence of a noise 50 50  (star) component in the fitted mixture model. It is mostly relevant 51 51  for models with a single tree component, since it is assumed that mixture models with 52 - at least two components always have the noise as a first component.} 52 + at least two components always have the noise as a first component. 53 + } 53 54  } 54 55   55 56  \value{
 ... ... @@ -14,28 +14,29 @@ 14 14  have to be specified. 15 15  } 16 16  \usage{ 17 -generate(K, no.events, noise.tree = TRUE, equal.edgeweights = TRUE,  18 - prob = c(0, 1), seed = (-1)) 17 +generate(K, no.events, \dots) 19 18  } 20 19  \arguments{ 21 20  \item{K}{An \code{integer} larger than 0 specifying the number of 22 21  branchings in the mixture model.} 23 22  \item{no.events}{An \code{integer} larger than 0 specifying the number of 24 23  genetic events in the mixture model.} 25 - \item{noise.tree}{A \code{logical} indicating the presence of a noise 24 + \item{\dots}{ 25 + \code{noise.tree} is a \code{logical} indicating the presence of a noise 26 26  (star) component in the random mixture model. The default value is 27 - \code{TRUE}.} 28 - \item{equal.edgeweights}{A \code{logical} specifying whether to use 27 + \code{TRUE}. 28 + \code{equal.edgeweights} is a \code{logical} specifying whether to use 29 29  equal edge weights in the noise component. The default value is 30 - \code{TRUE}.} 31 - \item{prob}{A \code{numeric} vector of length 2 specifying the 30 + \code{TRUE}. 31 + \code{prob} is a \code{numeric} vector of length 2 specifying the 32 32  boundaries for the edge weights of the randomly generated trees. The 33 33  first component of the vector (the lower boundary) must be smaller 34 34  than the second component (the upper boundary). The default value 35 - is (0.0, 1.0).} 36 - \item{seed}{A positive \code{integer} specifying the random generator 35 + is (0.0, 1.0). 36 + \code{seed} is a positive \code{integer} specifying the random generator 37 37  seed. The default value is (-1) and then the time is used as a 38 - random generator.} 38 + random generator. 39 + } 39 40  } 40 41  \value{ 41 42  The method returns an \code{RtreemixModel} object that represents the
 ... ... @@ -22,13 +22,7 @@ 22 22  } 23 23   24 24  \usage{ 25 -gps(model, ...) 26 - 27 -\method{gps}{model, data}(model, data, sampling.mode = "exponential", 28 - sampling.param = 1, no.sim = 10, seed = (-1)) 29 - 30 -\method{gps}{model}(model, sampling.mode = "exponential", 31 - sampling.param = 1, no.sim = 10, seed = (-1))  25 +gps(model, data, \dots)  32 26  } 33 27   34 28  \section{Methods}{\describe{ ... ... @@ -48,17 +42,19 @@ gps(model, ...) 48 42  containing the samples (patterns of genetic events) for which the GPS values 49 43  are to be calculated. The length of each of them has to be equal 50 44  to the number of genetic events in the \code{model}.} 51 - \item{sampling.mode}{A \code{character} that specifies the 45 + \item{\dots}{  46 + \code{sampling.mode} is a \code{character} that specifies the 52 47  sampling mode ("constant" or "exponential") used in the waiting time 53 - simulations. Its default value is "exponential".} 54 - \item{sampling.param}{A \code{numeric} that specifies the 48 + simulations. Its default value is "exponential". 49 + \code{sampling.param} is a \code{numeric} that specifies the 55 50  sampling parameter corresponding to the sampling mode given by 56 - \code{sampling.mode}. Its default value is 1.} 57 - \item{no.sim}{An \code{integer} larger than 0 giving the number of 58 - iterations for the waiting time simulations. Its default value is 10.} 59 - \item{seed}{A positive \code{integer} specifying the random generator 51 + \code{sampling.mode}. Its default value is 1. 52 + \code{no.sim} is an \code{integer} larger than 0 giving the number of 53 + iterations for the waiting time simulations. Its default value is 10. 54 + \code{seed} is a positive \code{integer} specifying the random generator 60 55  seed. Its default value is (-1) and then the time is used as a 61 - random generator.} 56 + random generator. 57 + } 62 58  } 63 59   64 60  \value{ ... ... @@ -76,7 +72,7 @@ gps(model, ...) 76 72  The mixture model used for deriving the GPS values should not have more than  77 73  20 genetic events. The reason for this is that the number of all possible patterns  78 74  for which the GPS values are calculated during a computationally intensive simulations  79 - is in this case $2^{20}$. This demands too much memory. 75 + is in this case $2^20$. This demands too much memory. 80 76  The GPS examples are time consuming. They are commented out because of the time restrictions of the check of the package. 81 77  For trying out the code please copy it and uncomment it. 82 78  }
 ... ... @@ -19,14 +19,17 @@ 19 19  }  20 20   21 21  \usage{  22 -plot(x, k, fontSize = 8)  22 +plot(x, y, \dots)  23 23  }  24 24   25 25  \arguments{  26 26  \item{x}{An \code{RtreemixModel} object giving the mixture model that should be visualized.}  27 - \item{fontSize}{The size of the text labels of the nodes and the edges of the tree components. The default value is 8.}  28 - \item{k}{A \code{numeric} giving the specific tree component from the given mixture model that should be plotted. Its value  29 - can be from one to the number of tree components in the given model.}  27 + \item{y}{Not specified.}  28 + \item{\dots}{  29 + \code{fontSize} is the size of the text labels of the nodes and the edges of the tree components. The default value is 8.  30 + \code{k} is a \code{numeric} giving the specific tree component from the given mixture model that should be plotted. Its value  31 + can be from one to the number of tree components in the given model.  32 + }  30 33  }  31 34  \value{  32 35  The method returns a plot of the mixture model model. 
 ... ... @@ -14,13 +14,7 @@ 14 14  patterns together with their waiting and sampling times from the respective model. 15 15  } 16 16  \usage{ 17 -sim(model, ...) 18 - 19 -\method{sim}{model}(model, no.draws = 10, seed = (-1)) 20 - 21 -\method{sim}{model, sampling.mode, sampling.param}(model, sampling.mode,  22 - sampling.param, no.sim = 10, 23 - seed = (-1)) 17 +sim(model, sampling.mode, sampling.param, \dots) 24 18  } 25 19   26 20  \arguments{ ... ... @@ -32,14 +26,16 @@ sim(model, ...) 32 26  \item{sampling.param}{A \code{numeric} that specifies the 33 27  sampling parameter corresponding to the sampling mode given by 34 28  \code{sampling.mode}.} 35 - \item{no.draws}{An \code{integer} larger than zero specifying the 36 - number of patterns that should be drawn from the given mixture model.} 37 - \item{no.sim}{An \code{integer} larger than 0 giving the number of 29 + \item{\dots}{ 30 + \code{no.draws} is an \code{integer} larger than zero specifying the 31 + number of patterns that should be drawn from the given mixture model. 32 + \code{no.sim} is an \code{integer} larger than 0 giving the number of 38 33  iterations for the waiting time simulations. Its default value is 39 - 10.} 40 - \item{seed}{A positive \code{integer} specifying the random generator 34 + 10. 35 + \code{seed} is a positive \code{integer} specifying the random generator 41 36  seed. Its default value is (-1) and then the time is used as a 42 - random generator.} 37 + random generator. 38 + } 43 39  } 44 40   45 41  \value{