Multinomial probit regression with mixed type explanatory variables

Multinomial probit regression with mixed type explanatory variables

By : user2172869
Date : October 22 2020, 08:10 PM
hope this fix your issue I have a data frame called aggregates composed of numerical columns each having a significant amount of zero values. I want to fit a probit model for each column by regressing them on another data frame called exp_vars. exp_vars is composed of factors, ordered factors, integers and numbers. I tried this: , The problem is indeed about the formula. The following works
code :
lapply(aggregates , function(y) glm(y ~ . ,family = binomial(link = "probit"), data = cbind(y = y, exp_vars)))
data = cbind(y = y, exp_vars)
cbind(y = 1:5, exp_vars)
#   y exp1 exp2 exp3
# 1 1   21   11    1
# 2 2   22   12    0
# 3 3   23   21    0
# 4 4   24   22    1
# 5 5   25   23    1

Share : facebook icon twitter icon
Linear Regression in R with variable number of explanatory variables

Linear Regression in R with variable number of explanatory variables

By : user3776390
Date : March 29 2020, 07:55 AM
around this issue , Three ways, in increasing level of flexibility.
Method 1
code :
fit <- lm( Y ~ . , data=dat )
dat <- cbind(data.frame(Y=Y),as.data.frame(X))
fit <- lm( Y~. , data=dat )
model1.form.text <- paste("Y ~",paste(xvars,collapse=" + "),collapse=" ")
model1.form <- as.formula( model1.form.text )
model1 <- lm( model1.form, data=dat )
Poisson regression with both response and explanatory variables as counting

Poisson regression with both response and explanatory variables as counting

By : elviiis04
Date : March 29 2020, 07:55 AM
wish helps you The problem seems like it could be well modeled with Poisson regression. The residual variance should NOT be "homogeneous". The Poisson model assumes that the variance is proportional to the mean. You have options if that asumption is violated. The quasi-biniomial and the negative binomial models can also be used and they allow some relaxation of the dispersion parameter estimates.
If the number of quota units owned by fishers sets an upper bound on the number used then I would not think that should be used as an explanatory variable, but might better be entered as offset=log(quota_units). It will change the interpretation of the estimates, such that they are estimates of the log(usage_rate).
linear regression with compositional explanatory variables

linear regression with compositional explanatory variables

By : Carlos Eduardo Ferre
Date : March 29 2020, 07:55 AM
will help you You can remove any one of the variables and perform standard linear regression. The reason is that given n-1 variables, you can uniquely determine your nth variable. Thus, the nth variable is not required.
Is there a way of identifying the values of explanatory variables in a logistic regression at the end of a function?

Is there a way of identifying the values of explanatory variables in a logistic regression at the end of a function?

By : user2735301
Date : March 29 2020, 07:55 AM
this one helps. I have a matrix called all.confusion.tables which contains a table of predicted values versus actual values for explanatory variables. I then apply a misclassification rate function to this and it gives me an output which looks like , Simple stuff:
code :
x <- rnorm(8) # some dummy data
setNames(x, c("age","lwt", "race", "smoke", "ptl", "ht","ui","ftv"))
Naming explanatory variables in regression output

Naming explanatory variables in regression output

By : La Vara
Date : March 29 2020, 07:55 AM
I wish this helpful for you Searching through the source, it appears the summary() method does support using your own names for explanatory variables. So:
code :
results = sm.OLS(y, X).fit()
print results.summary(xname=['Fred', 'Mary', 'Ethel', 'Bob'])
                                OLS Regression Results
Dep. Variable:                      y   R-squared:                       0.535
Model:                            OLS   Adj. R-squared:                  0.461
Method:                 Least Squares   F-statistic:                     7.281
Date:                Mon, 11 Apr 2016   Prob (F-statistic):            0.00191
Time:                        22:22:47   Log-Likelihood:                -26.025
No. Observations:                  23   AIC:                             60.05
Df Residuals:                      19   BIC:                             64.59
Df Model:                           3
Covariance Type:            nonrobust
                 coef    std err          t      P>|t|      [95.0% Conf. Int.]
Fred           0.2424      0.139      1.739      0.098        -0.049     0.534
Mary           0.2360      0.149      1.587      0.129        -0.075     0.547
Ethel         -0.0618      0.145     -0.427      0.674        -0.365     0.241
Bob            1.5704      0.633      2.481      0.023         0.245     2.895
Omnibus:                        6.904   Durbin-Watson:                   1.905
Prob(Omnibus):                  0.032   Jarque-Bera (JB):                4.708
Skew:                          -0.849   Prob(JB):                       0.0950
Kurtosis:                       4.426   Cond. No.                         38.6

[1] Standard Errors assume that the covariance matrix of the errors is correctly specified.
Related Posts Related Posts :
  • Authentication failure with rdrop2
  • DT data table display error
  • Issue when adding new rows (with nested dataframes within) to a dataframe
  • R-How to compare two dataframe and update list column value
  • Series vector for approximating pi
  • what is difference between "variance explained " in Random Forest and "merror" in XGBoost
  • R - Cast dataframe on unique rows - reshape2
  • ggplot2: plot correct proportions using geom_bar
  • Speedup query for R data.table - can this two-argument function be applied by group more quickly?
  • apply a function to several columns at once with mutate
  • R 'cowplot' neatly produce gridded plot with shared (common) legends and unique legends
  • Repeat R script for many times and save results to text file
  • How to negative lookbehind for special characters
  • data.table inner join produces error when no match is found
  • Create a new column base on existing column, but row above
  • Is there a way to visualize the process of source() in RStudio?
  • google places api consumes 10 request but I am doing only 1
  • Statistical mode of a categorical variable in R (using mlv)
  • Using for-loop to mutate a data.frame in r
  • Make plot with regression line for mixed model
  • Shortcut to select matces cases in R studio
  • vectoriced norm/matrix multiplication
  • Negative log10 transformation in R
  • Plot data with duplicate points
  • Visualizing crosstab tables with a plot in R - changing colours
  • How to manually modify automated numbers and labels in plot
  • How can I follow any redirections of a url in R?
  • Add jitter to box plot using markers in plotly
  • Adding an extra item to the legend
  • ggplot fills in data in the wrong order
  • Convert list to data frame
  • R: filtering by list(s) of strings and returning all results that start with the content of the lists
  • R:How to attach parts of a data frame with different headers and/or an overflowing piece of the dat frame
  • How to use 'par' for manipulating plot margins?
  • Can dplyr::case_when return mix of NAs and non-NAs?
  • Text preprocessing and topic modelling using text2vec package
  • Uploading multiple files in Shiny, process the files, rbind the results and return a download
  • R levelplot: color green-white-red (white on 0) according to one variable, but show the values of another variable
  • Why [i] doesn't point to the starting point in a vector
  • In R after generating a mvrnorm distribution, Y, what does Y[,1] do?
  • expand a data frame to have as many rows as range of two columns in original row
  • Getting started with R and CFA
  • Re order x-axis in ggplot so time goes from 12AM to 11PM in R
  • R - Automatically stack every nth column of a data frame and save them as new objects
  • How to format dplyr output in R into doubles (or other workable format)?
  • Dataframe to matrix conversion using tapply turns zeros to NAs
  • Smallest multiple of 1:20 - How can I make it quicker?
  • How to specify the size of a graph in ggplot2 independent of axis labels
  • How can I find the number of a vector's elements in another vector?
  • ROC curve from train/test set in caret R package
  • Random Forest for a mixture of categorical,numeric and "unwanted" variables which include missing values
  • extract certain data from multiple excel files with R
  • Matrix with counts of wins and losses between methods in R
  • Grouping string variables from a dataframe by best string match to make subsets
  • Reorder does not work after adding second geom_points
  • cover POS data formate to the one can apply Arules (Apriori)
  • Matching values between data frames based on overlapping dates
  • Grouped bar chart turns into stacked bar chart ggplot
  • R: How to fill in NA Values within a Column based on grouping?
  • Two action buttons, but only the first one, that is written in the server file, works?
  • shadow
    Privacy Policy - Terms - Contact Us © voile276.org