Buenas tardes: Necesito un experto en lenguaje de programación R con conocimientos en estadística aplicada. Indispensable hablar español. El deadline es en 24 horas Muchas gracias y saludos
Modelling and Pricing of Options under Constant elasticity of variance CEV Models 1- option price 2- r Constant elasticity of variance CEV Models 3- ggm model
project is to apply appropriate machine learning R , with any topic/problem related to large dataset processing and analytics. You need to analyse requirements, formulate solution, and implement your solution in the form of software development . Finally you need to present all your project and results in a written technical report.
I need practical exercises related to business and making decisions. I am teacher. I will teach R languaje for statistical. But I need data and real problems to can explain how R can resolve all kind of problems related to business and making decisions. I need exercises with resolution guide and explanations to can resolve in 12 hours.
I am looking a suggestion for the best approach to model - 12 questioner (Ordinal - score of 0 to 4 – its the level of implementation intervention) and continuous outcome. Requires SAS STATS/ SAS Macro knowledge as well– May be one hour consultation. I already have something in place but just want get second opinion. Thanks
data analysis: Descriptive and regression analysis
The project requires one-variable or two-variable analysis. The key question here is what is a variable? A variable is something that is changeable, and we need to define it before we can perform the analysis. The assignment has no restrictions on how to define a variable. For example, we can define a variable as "the unemployment rate", then it's a variable containing a sequence of numbers across many years. However, since it is one-variable, we only see a set of nunmbers, without any year information. 2. Once you have a clear definition of a variable, you need to pick up the data cells for further graphing and analysis. You can do cell selection inside R. Or to make it simpler, you can use Excel to select the data cells about the variable, and save them to a new csv file, and read the file into R later. Either method is ok for the assignment. 3. Some failed to get the plots as expected. This is mainly due to the data frame structure used in R. For example, I decided to select the unemployment row. Even if I just select one row, and it looks like a sequence of numbers, it is in fact a data frame. As a data frame, each column is considered as a vector or variable. And this unemployment consists of multiple variables/vectors. If I plot this row directly, I will not get the chart I'm looking for. ... Series Name Series Code 1995 [YR1995] 1996 [YR1996] 1997 [YR1997] 1998 [YR1998] 1999 [YR1999] 2000 [YR2000] 2001 [YR2001] 2002 [YR2002] ...... Unemployment, total (% of total labor force) (modeled ILO estimate) [login to view URL] 8.5 8.5 8.399999619 7.699999809 6.900000095 6.300000191 ... The solution is to: Transpose the data frame, or Create a pure vector of numbers from the row, or Use Excel to select the cells and create a new csv in the correct data frame format, or etc... 4. For clustering and linear regression, you also need to clearly define the variables you are studying. Defining the problem is always the first step for any data analysis.
The Santa Fe Institute Press seeks a graphic designer for an upcoming book featuring extensive data visualization in R and/or Stata. The designer would be responsible for working with authors to produce high-quality, visually consistent graphics for both print and ebook distribution. The project is slated to begin in summer 2018. For more information on the Santa Fe Institute, please visit https://santafe.edu.