R is an open source programming language for statistical computing and graphics, it is widely used by statisticians and data miners.雇佣 R Programmers
We offer multiple services to our customers and recently did a survey where the customers were asked about their satisfaction levels for all the services provided to them. They ranked the services at a scale from "very unsatisfactory" to "very satisfactory" based on different service indicators such as cost, wait time etc. I would like your help with the best analysis approach for this survey data. I will prefer candidates with previous experience in similar analysis. You will also be preferred if you explain how you will handle this problem and which analytical method/technique will you apply. Thank you
Statistical modelling- help with linear modelling and statistical language I will share the details in pm. thanks.
I need to use RStudio to program my own Kalman filter to estimate parameters for a Lee-Carter mortality model. I need to be able to obtain parameter estimates, and respective functions used in this estimation. I also need to be able to code the Kalman filter and all it’s other extensions by hand (I.e no built in packages). I have a basis code I have been working on which I would ideally like to have improved and then extended to meet the above requirements
I need someone help me carry out statistical analysis similar to the ones presented in this paper: Particularly: - there will be two groups, patients vs controls, propensity score matched - there will be a date for patients when the event occurred - there will be a longitudinal biomarker (weekle average of steps) for each patient and control - I want to see how the biomarker changes in the two groups with respect with the occurrence of the event as they did, with the wonderful plot they presented (also with the one with the standardized difference) You can carry out the analysis in R, SAS or Python I don't care, but in any case i need to have the code to check how you have done it
I have a dataset of 3,000 lines and 4,000 columns and the rows are grouped into 5 classes and I need to find out which columns, and combination of columns, are more discriminative for each combination of classes (re classifying into binary one versus the other or one combination versus all etc). The best would be to first find the combination of features most relevant for a class (the identity of the features is what is of interest here), and then building a model to find and test the accuracy for predicting a class from those features. I am looking for a machine learning expert in R so I can understand and replicate each step.
Interactive R Shiny dashboard for Genomics Data using 2 Bioconductor packages