Nope
Not whatsoever
Not at all, Schneider's EV program is a computer simulation of the algebraic model I've presented.
The difference between Schneider's computer simulation and the math I've presented is that he has 3 selection conditions that are acting simultaneously on the entire genome at multiple sites in the genome. This is why his algorithm will only adaptively evolve quickly on extremely short genomes (256 bases) with an extremely high mutation rate when all three selection conditions are acting.
Tell that to the scientists and population geneticists. Oh sorry, you have already done that over and over ad nauseam with the same result.
I actually have a computer simulation of my model but macroevolutionists don't trust my algebra and application of probability theory to this system. Why would they believe my computer simulation. Anyway, experimental data is the key to testing the validity of a mathematical model. At least I have two "isolated" lab experiments to test the model. Of course I also have all the empirical data starting with the successful use of 3 drug therapy to treat HIV.
Do you really want to stake your reputation on a 2bit review in a 2bit journal of 2 isolated lab experiments that you piggy backed on to create a model that you take to forum after forum in self-promotion and no one but anti-evolutionists are buying? You done that too with the same result.
Do you mean that observational "science" that you won't give the best example of observation?
Did your dad ever tell you when you are in a hole to stop digging?
You need to get up to date with actual science and away from your fables.
Evolvability and the Fossil Record
Abstract
The concept of evolvability—the capacity of a population to produce and maintain evolutionarily relevant variation—has become increasingly prominent in evolutionary biology. Although paleontology has a long history of investigating questions of evolvability, often invoking different but allied terminology, the study of evolvability in the fossil record has seemed intrinsically problematic. How can we surmount difficulties in disentangling whether the causes of evolutionary patterns arise from variational properties of traits or lineages rather than due to selection and ecological success? Despite these challenges, the fossil record is unique in offering growing sources of data that span millions of years and therefore capture evolutionary patterns of sustained duration and significance otherwise inaccessible to evolutionary biologists. Additionally, there are a variety of strategic possibilities for combining prominent neontological approaches to evolvability with those from paleontology. We illustrate three of these possibilities with quantitative genetics, evolutionary developmental biology, and phylogenetic models of macroevolution. In conclusion, we provide a methodological schema that focuses on the conceptualization, measurement, and testing of hypotheses to motivate and provide guidance for future empirical and theoretical studies of evolvability in the fossil record.
You also need to get up to date on simulations
Evolutionary Modeling in SLiM 3 for Beginners
Abstract
The SLiM forward genetic simulation framework has proved to be a powerful and flexible tool for population genetic modeling. However, as a complex piece of software with many features that allow simulating a diverse assortment of evolutionary models, its initial learning curve can be difficult. Here we provide a step-by-step demonstration of how to build a simple evolutionary model in SLiM 3, to help new users get started. We will begin with a panmictic neutral model, and build up to a model of the evolution of a polygenic quantitative trait under selection for an environmental phenotypic optimum.