Survival-analysis | survival analysis , predictive maintenance | Machine Learning library

I am using the R programming language. I am trying to follow this tutorial over here: https://rviews.rstudio.com/2017/09/25/survival-analysis-with-r/ (bottom of the page).

I have slightly modified the code for this tutorial and have plotted the "staircases" (i.e. "survival functions", in the below picture "red", "blue", "green") corresponding to 3 of the observations in the data:

I am trying to follow a tutorial in R (https://rviews.rstudio.com/2017/09/25/survival-analysis-with-r/).The computer I am using for work does not have a USB port or internet connection - it only has R with a few libraries installed. My work computer has "survival, ranger, ggplot2 and dplyr". However, it does not have "ggfortify". I am trying to figure out how to plot the graphs from the tutorial without 'ggfortify'. Here is the code I am using below:

I am following a R tutorial over here https://rviews.rstudio.com/2017/09/25/survival-analysis-with-r/

The computer I use for work does not have internet access nor a USB port - it only has R with some preinstalled libraries. The tutorial requires "survival", "ggplot2", "ranger", "dplyr" and "ggfortify". The computer I use for work has all of these libraries EXCEPT ggfortfiy. Apparently, a function called "autoplot" is required from the ggfortify library to make some of the plots in this tutorial.

When I try to run the code from the tutorial:

I am a newbie in using and making sense of ML methods and currently doing survival analysis using gbm package in R.

I have difficulty understanding some of the output of the survival prediction model. I have checked this tutorial and this post but still, find trouble in making sense of the outputted survival prediction model.

Here is my code for analysis based on example data:

Unfortunately I am not a programmer and I am encountering the error:

I just recently started to learn shiny.

Overview of this question: (1) How it works in R incl. script, (2) How it should work in Shiny, (3) Data

Question: where to write the shiny input$ID in this function to make it calculate the nomogram/nom-score based on the UI-inputs?

(1) How it works in R incl. script

I am performing survival-analysis, and I have produced a rather simple nomogram using the rms-package. The nomogram can be found below and is stored in nom.

The nomogram currently looks like this:

The nomogram is based on some input covariates from my datasheet p ( which too is attached below [just as a sample]).

I am doing survival-analysis with the presence of competing risks. I use the prodlim-package, which I find quite useful. However, I do not like the build-in graphics, and would like to apply ggplot instead.

Question: how can I extract the prodlim summary()-output and load it into a data frame accessible to ggplot2?

Perhaps a function can be written to do this? I have previously received help on StackOverflow in terms of loading a summary()-output into a dataframe, but with a different package than prodlim.

I am working on a regular customer survival analysis problem. Here I analyze customers who signed up between 2008-1-1 & 2018-1-1. Customers can register anytime during this interval and exit anytime during or after the cut-off date of 2018-1-1.

A sample data is shown below. First column is an identifier, second column is their status as of 2018-1-1: '1 for canceled & 0 for not-cancelled'. Third column is the number of weeks between their registration date & 2008-1-1. Last column is the number of weeks between their cancellation date and 2008-1-1 (if cancelled before 2018-1-1) or number of weeks between 2008-1-1 and 2018-1-1 (if not cancelled or cancelled after 2018-1-1).

dput() to generate the above dataset

I have previously tried to ask for help but did not actually solve my problem. More info can be found here: (you can find the data-set here) https://stackoverflow.com/questions/51442502/survival-analysis-combining-survfit-and-ggplot-objects

Unfortunately I am unable to produce a solid example to post as my code is heavily based on external programs. I am positive though that my question can be answered regardless.

I reach a point where I create 2 ggplot2 objects that need to be combined to a single figure, one overlayed on top of the other.

Namely, one km.plot which is of class:

class(km.plot$plot)
1 "gg" "ggplot"

and two:

class(surv.plot)
1 "gg" "ggplot"

Both share same attributes

km.plot$plot

surv.plot

My question is how can I combine the resulting plots in a single plot? That is, to have both surv.plot and km.plot$plot overlayed over each other.

Following another user's suggestion of doing the following results in an error: