Parsimony programs

Hennig86 was written by James S. Farris (American Museum of Natural History, New York, NY 10024). It is a fast and effective parsimony program. It is often faster than PAUP but has many fewer features and options. However, Hennig86 does contain a routine for successive approximation a posteriori character weighting. 

The third (default) method uses a table of empirically observed transitions between amino acids (the Dayhoff PAM 001 matrix). The character-based analysis of sequence data can be initiated via the appropriate executable file (e.g. DnaPars, DnaML or ProtPars). PHYLIP comprises DnaPars and DnaML to estimate phylogenetic relationships by the parsimony method and the maximum likelihood methods from nucleotide sequences respectively. ProtPars is the parsimony program for protein sequences. 

The result is a parsimonious framework with intuitive appeal that supports investments in customer satisfaction programs and customer loyalty programs. To counter-balance the linkages discussed above, the cost impact of the vendor s customer management effort can be implicitly (e.g. Heskett, et al., 1994) or explicitly (e.g. Bowman Narayandas, 2004 Kamakura, Mittal, de Rose, Mazzon, 2002) accounted for. 

Finally, many complex software programs are modified or evolved from other programs. The result may be convoluted dead end pathways, nonfunctioning dead code, and inefficient module looping structures. Examination of code to determine the elegance or simphcity that avoids these non-parsimonious problems provides an important element in the evidence supporting continued reliabihty. 

D. L. Swofford, PAUP Phylogenetic Analysis Using Parsimony, Version 3.1. Computer program distributed by the Illinois Natural History Survey, Champaign, Illinois, 1993. 

In view of such developments, it is not surprising that there have been several attempts in 1985-1989 to reconsider the evolutionary relationships. The approach in many studies has been to construct parsimony trees using methods and computer programs based essentially on the maximum parsimony methods of Farris (1970, 1972) or Fitch and Mar-... 

Parsimony. The complexity of the models and simulation procedures should be no more complex than necessary to meet the objectives of the simulation project. Program codes sufficient to generate models, simulate trials, and perform rephcation and simulation project level analyses should be retained but there is no need to store simulated trials and analysis results that can be reproduced from these codes (3). 

The SA may also provide rationale for simplifying a model. This may occur if the outcome is shown to be robustly tolerant to wide ranges of parameter uncertainty, which may allow for the removal of some parameters and thus lead to a more parsimonious simulation model. Conversely, the SA may reveal that insufficient information currently exists to define a precise or reliable range of trial outcomes. In this latter case, either more time may be required to obtain additional informative experimental data and thus reduce the uncertainty to an acceptable range, or separate sets of plausible assumptions may need to be considered and subsequently tested for their own sensitivity. Such decisions need buy-in from the subject matter experts and should be considered in the full context of the development program. 

Several phylogenetic analysis programs use a generalized parsimony method in which the user (Swofford 1990, Maddison and Maddison 1990) or the program (Williams and Fitch 1989) defines a matrix which describes the cost associated with a transition from state i to state j.. Modification of the cost matrix allows experimentation with different kinds of weighting. 

The search for the shortest trees in tree space and the use of the cladistic version of the principle of parsimony, as implemented in computer programs... 

The cladistic parsimony principle, as understood by most users of computer programs, is utilized only in the search for the shortest tree. I have frequently heard cladists say that it should be impossible to discover an optimal tree topology by hand when many species are being considered, because there are millions of alternative topologies to be considered (e.g., about two million unrooted topologies for only 10 terminal taxa). As there exist more than 900,000 known species of insects and the number of alternative topologies that... 

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