R programming for linear model
model2<lm(formula = Losses.in.Thousands~Age, Years.of.Experience,Gender, Married, data = default)
Error in model.frame.default(formula = Losses.in.Thousands ~ Age, data = default, : object 'Married' not found
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Add Hive odbc driver to server
I'm using hosted RStudio on Red Hat CentOs7.
I would like to connect to a Hive database and was looking at odbc package after reading a how to blog page on rstudio.
Example code from the page:
library(odbc) con < dbConnect(odbc::odbc(), driver = <driver>, host = <host>, dbname = <dbname>, user = <user>, password = <password>, port = 10000)
This is my current objective, to create a connection to Hive. The part that's tripping me up is the driver.
On the Horton Works add ons page I copied a link to CENTOS7 (64Bit) driver: https://publicrepo1.hortonworks.com/HDP/hiveodbc/2.1.16.1023/Linux/EL7/hiveodbcnative2.1.16.10231.el7.x86_64.rpm
Then, on my linux server:
sudo wget https://publicrepo1.hortonworks.com/HDP/hiveodbc/2.1.16.1023/Linux/EL7/hiveodbcnative2.1.16.10231.el7.x86_64.rpm sudo yum install hiveodbcnative2.1.16.10231.el7.x86_64.rpm
Everything appeared to work OK up till this point.
I added the driver to the con call:
con < dbConnect(odbc::odbc(), driver = 'hiveodbcnative2.1.16.10231.el7.x86_64', host = 'example.com', dbname = 'mydb', user = 'doug', password = 'password123', port = 10000)
However, R tells me: "Error: nanodbc/nanodbc.cpp:950: 01000: [unixODBC][Driver Manager]Can't open lib 'drivers/hiveodbcnative2.1.16.10231.el7.x86_64' : file not found ".
How can I use this obdc driver for my connection?

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I am trying to understand how to use the R package glmnet.
Suppose I have a dataset, representing games played between two teams, with the 'win' column defining the result.
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I now want to run this data through glmnet, with the 'won' column as the response.
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I'm trying to run a multiple regression model looking at the lengthweight relationship in fish. So y = weight, x = weight. What I want to examine specifically is if the lengthweight relationship between different populations (same species) differs  I've run the model as:
weight = length * population
BUT have also reading a lot about centering data in regression models. It seems to make no sense to me to grandmean centre length for this analysis as i'm specifically interested in the differences in LW relationship between the groups, but should I groupcentre for length? Or, not centre at all?
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I have some data that with two independent variables and one dependent. I'm using SPSS and my IVs have interaction. My results are below.
I don't have a stats background and am new to LG, so not sure how to interpret my results. Specifically, as I highlight below, the data seems to have significance (χ2(1) = 7.737, p = .005), but the Overall Percentage for the model is the same as the Null Hypothesis (60.0)?
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I am new to optimization so please bear with me. Here is my problem:
A, B, C, D and E are percentages (18%,2%,1%,78%,1%)
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We have a Linear Programming Problem. Currently we are solving this problem with Simplex method in our .NET desktop application.
We are planning to use Microsoft Solver in our application.
With reference to this link, we have following questions:
 Is the product still active?
 Does the product have enterprise level support for active users?
 We have seen the latest update on nuget (in January 2017). Is Microsoft planning for any new release in near future?
It would be great if anyone can provide any additional information or pointers regarding the product.