![]() ![]() "We are very knowledgeable and have a lot of experience," said Parisi. One of The Finicky Framer's specialties is frame restoration, a simple but effective process of taking in old paintings and pictures belonging to customers and refurbishing them with quality and accuracy. This gave me a big advantage because I knew the business already." I had two years of on-the-job training, plus five years of experience in retail. "Being an employee of the business for two years had a major impact on keeping the business running in a successful way. "I had a major decision to make about my career path," said Parisi. In 1989, the owners made her an offer to sell her the business, which she accepted. Just having the experience and being taught in school about all that stuff helps because it is an important part of what I do here in the store."Īfter graduating, Parisi started working for The Finicky Framer as an employee for two years. ![]() "You need to have that kind of background to help a customer design picture framing and to be able to enhance their picture to make it work in their home. "That was an interest of mine since I was a kid. Parisi has owned The Finicky Framer for 26 years, starting out soon after graduating as an art student looking to hone her creative skills and talents.Īfter earning a bachelor's degree in art and getting an education at Stockton State College in 1986, Parisi was ready to go out into the world and continue on her creative path. I started advertising out to areas such as Colts Neck and Holmdel to try and bring them to my location." "I did all different types of advertising, even in the slow time, which I think helped. "I never stopped advertising," said Parisi. One way that Parisi demonstrated her resourcefulness was by extending her advertising locales. As you can see, the proportion of highly biased estimates decreased greatly, but there are still some there, and again only in the N = ~ 120 - 140 range.SHREWSBURY – The Great Recession was a tough time for business owners, including Dana Parisi, owner of The Finicky Framer.ĭuring 20, Parisi went through a slow time and hit some low points as well. I decreased that to 1%.Ģ) I included one bin beyond the furthest observation in each dataset (by changing the function defining the breaks to:īreaks <- c(0, round((max(y$distance+1)/cats)*(1:(cats +1))))ģ) I included a wider range of sample sizes, just to see what would happen. ![]() This morning I tried a few things to see if I could fix it:ġ) In the above example I was truncating the furthest 10% of data. (Note that I capped bias at 2 so that the blue gam() line fit on the plot.) When simulating a lot of datasets (in the same way I produced the dataset in my original post) and analyzing the results, the bias looks like this: Obviously, there might be an error somewhere else in my code (but I haven't been able to figure out where.). With the data that I'm simulating, it only seems to be an issue when the sample size is between ~ 122 and 148 observations. I noticed that the estimates look fairly flat (at a glance), but I'm not convinced that entirely explains the issue. Unmarked.estimates <- ame(Item = c("density", "sigma"),Įstimated = c(unmarkeddensity_bias, unmarkedsigma_bias)) Unmarkedsigma <- backTransform(hn_Null, type='det') # extract estimate of detection parameter & calculate bias Unmarkeddensity <- backTransform(hn_Null, type="state") # extract density estimate & calculate bias # 2 different options for distance breaks. ![]()
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