Publications by Real R Application
Stock Analysis
bpe 313: Boeing Stock Visualization bambangpe — March 13, 2019 Intro text Trend Analysis This dashboard only displays the movement of shares of 2 Boeing (BA) and Airbus (EADSY) airlines, observing the movements of Boeing's shares after the tragedy of the fall of a Boeing 737 Max8 aircraft. Trends are taken in a 1 year period Boeing ...
1036 sym
Asset Regression use FAMA
Fama-Macbeth regression is a two steps procedure. In the first step, it runs cross-sectional regression at each point of time; the second step estimates the coefficient as the average of the cross-sectional regression estimates (Fama & MacBeth, 1972). Upload library ## Warning: package 'plm' was built under R version 4.0.5 ## Loading required pa...
406 sym R (1953 sym/14 pcs)
Forecast Military Expenditures for the next 5 years
The objective of this analysis is an estimate of military expenditure over a period of 5 years, by determining which one is the best model, ETS, HoltWinters or Arima? library(dplyr) library(lubridate) library(forecast) library(TTR) library(ggplot2) library(tseries) Accuracy ETS model ds <- read.csv("d:/UPWORK-IRL-1/dn_clean_ts_1.csv") ds02...
605 sym R (4453 sym/28 pcs) 3 img
Forecast
Upload library #library(scales) #library(zoo) library(forecast) library(tseries) library(fpp) library(ggplot2) library(dplyr) Upload data/df.csv d <- read.csv("d:/UPWORK-IRL/df.csv") head(d,3) ## X Name Year hdi me_normalized me ## 1 1 Algeria 1990 0.572 20.62263761 904269155 ## 2 2 Argentina 1990 0.718 21.441548...
552 sym R (8062 sym/22 pcs) 2 img
H2O automl analysis
Analysis save energy by building good model based on human comfort and other factors Use data Smart WiFi Thermostat Enabled Thermal Comfort Control in Residences library(readr) dt <- read_csv("d:/FREELANCE-USA/Additional resources for project/R Scripts/DF21.csv") #dim(dt) #[1] 14041 16 dt <- dt[,-c(1:5)] sum(is.na(dt)) #[1] 6 ## [1] 6 dt1...
291 sym R (8377 sym/19 pcs) 15 img
PMV Analysis 2nd-exp
Use Data DF2 library(data.table) #library(lubridate) library(tidyverse) library(knitr) library(readr) Upload data df21 <- read_csv("D:/FREELANCE-USA/Additional resources for project/dataset/DF21.csv") ## ## -- Column specification -------------------------------------------------------- ## cols( ## .default = col_double() ## ) ## i ...
245 sym R (7248 sym/28 pcs) 1 tbl
Confort Thermal Analysis
Use Data DF21 library(data.table) #library(lubridate) library(tidyverse) library(knitr) library(readr) Upload data df21 <- read_csv("D:/FREELANCE-USA/Additional resources for project/dataset/DF21.csv") ## ## -- Column specification -------------------------------------------------------- ## cols( ## .default = col_double() ## ) ## i...
297 sym R (8740 sym/29 pcs) 1 tbl
Clustering use PCA
1. The data We will analyze the "The file ‘Childbirths’ contains data on childbirths in a US city." consists of 42 observations and 16 variables (target and predictors variable), the model to be used is a logistic model. 1.2 About PCA To make exploratory data analysis, we use Principal Component Analysis (PCA) for preprocess data.PCA ...
667 sym R (7615 sym/35 pcs) 2 img
PMV-02
Use Data DF2 library(data.table) #library(lubridate) library(tidyverse) library(knitr) library(readr) Upload data df21 <- read_csv("D:/FREELANCE-USA/Additional resources for project/dataset/DF21.csv") ## ## -- Column specification -------------------------------------------------------- ## cols( ## .default = col_double() ## ) ## i ...
245 sym R (7185 sym/28 pcs) 1 tbl
Top Movies
We’ll pull data about movie sales from the “boxoffice” data source (for which we installed the boxoffice package above). First we have to decide what time frame we want the data for. Upload library Define time periods for which to collect data In this case set start from 2015 to 2020 date.seq <- paste(2015:2020,"-12-31",sep="") date.seq ...
1042 sym R (6332 sym/19 pcs) 1 img 1 tbl