I'm currently doing arima forecasting in R and i'm already on the last step of displaying the forecast result but I am having trouble in displaying the forecast on the graph.
Here is my code:
mydata.arima005 <- arima(d.y, order= c(0,0,5))
mydata.pred1 <- predict (mydata.arima005, n.head =100)
plot(d.y)
lines(mydata.pred1$pred, col="blue")
lines(mydata.pred1$pred+2*mydata.pred1$se, col="red")
lines(mydata.pred1$pred-2*mydata.pred1$se, col="red")
So as you can see, I want my graph to show the forecast values in color blue and the confidence interval on red. But this is what I am getting instead.
So as you can see it's not color coded at all. My code contains no error.
This is a sample of the output I am expecting(got it from youtube)I used the same codes used in this video I got thats why i was wondering why my graph doe not look like this.Hope you could help
The forecast package has some functions for displaying nice plots of the forecasts and prediction intervals.
You would need something like this:
library(forecast)
mydata.arima005 <- Arima(d.y, order= c(0,0,5))
mydata.pred1 <- forecast(mydata.arima005, h=100)
plot(mydata.pred1)
Or using ggplot2 graphics:
library(ggplot2)
autoplot(mydata.pred1)
Related
I am working with data where I need to create multiple scatter plots for different populations. I also recently upgraded from SPSS v26 to v28 and the code that I used for this worked in v26 but is no longer working correctly in v28. Instead of producing multiple scatter plots like it's supposed to, it is now producing 1 plot in v28, presumably the first subpopulation in the split. I tested the split file function with descriptives and it worked as intended.
I have scoured everything in the GUI menus to find any kind of setting that was ticked by default and came up with nothing. I also tried to use a filter based on the criterion variables in my split file function and ran a scatter plot but that gave me a graph of the whole population instead of the subpopulation I filtered. Any guidance on what could be going on with scatter plots and the split file function in SPSS v28 would be greatly appreciated.
Here is my code for reference:
SORT CASES BY exit_yr service sigscore.
SPLIT FILE SEPARATE BY exit_yr service sigscore.
*Chart Builder.
GGRAPH
/GRAPHDATASET NAME="graphdataset" VARIABLES=wait.time[name="wait_time"]
score.change[name="score_change"] service.ideal[name="service_ideal"] MISSING=VARIABLEWISE
REPORTMISSING=NO
/GRAPHSPEC SOURCE=INLINE
/FITLINE TOTAL=NO SUBGROUP=NO.
BEGIN GPL
SOURCE: s=userSource(id("graphdataset"))
DATA: wait_time=col(source(s), name("wait_time"))
DATA: score_change=col(source(s), name("score_change"))
DATA: service_ideal=col(source(s), name("service_ideal"), unit.category())
GUIDE: axis(dim(1), label("wait.time: Difference in days between referral submission ",
"and referral acceptance"))
GUIDE: axis(dim(2), label("score.change: score change from pre to post"))
GUIDE: legend(aesthetic(aesthetic.color.interior), label("service.ideal"))
GUIDE: text.title(label("Grouped Scatter of score.change: score change from pre to ",
"post by wait.time: Difference in days between referral submission and referral ",
"acceptance by service.ideal"))
ELEMENT: point(position(wait_time*score_change), color.interior(service_ideal))
END GPL.
SPLIT FILE OFF.
I have downloaded hourly stock data for AAPL for the past 30 days and am displaying a candlestick chart. The chart loads properly but the time shown for each bar is incorrect. I am in the Pacific time zone.
I tried changing the way the data table is created but none of the ideas below seem to help.
var dataTable = anychart.data.table(0);
var dataTable = anychart.data.table(0, '', 8);
I am using the same example as the one on the AnyChart website https://www.anychart.com/products/anystock/gallery/Stock_General_Features/Showing_Intraday_Data.php
Please see the following 2 images.
For the ORCL chart from the example on the AnyChart website, I clearly see the date and time (highlighted rectangle)
working example from AnyChart website
For my chart (for AAPL hourly data), the time is off and it shows "13 05 Nov 2021" etc.
Does not work for my data
My source CSV file contains data as below (full CSV available at this link)
timestamp,gmtoffset,datetime,open,high,low,close,volume
1634650200000,0,2021-10-19 13:30:00,147.009994,148.820007,146.550003,148.759994,24069759
1634653800000,0,2021-10-19 14:30:00,148.759994,149.169998,148.229995,148.384994,13899143
1634657400000,0,2021-10-19 15:30:00,148.380004,148.759994,148.220001,148.759902,7623131
1634661000000,0,2021-10-19 16:30:00,148.759704,149.044998,148.5,148.889999,6263260
1634664600000,0,2021-10-19 17:30:00,148.884994,148.979995,148.479995,148.535003,4807906
1634668200000,0,2021-10-19 18:30:00,148.539993,148.837295,148.330001,148.460006,6333632
....
Thanks to AnyChart for responding so quickly via email.
The following snippet solves the issue with the tooltips and now I can see the proper date and time on the tooltip.
chart.tooltip().titleFormat(function() {
return anychart.format.dateTime(this.x, 'yyyy-MM-dd HH:mm:ss');
});
To set the proper legend, the following code does it:
plot.legend().title().useHtml(true);
// configure the format of the legend title
plot.legend().titleFormat(
"<span style='font-weight:600'>" +
"{%hoveredDate}{dateTimeFormat: yyyy-MM-dd HH:mm:ss}</span>"
);
I am using Vincent to plot county level map for US. Took example data for 2016 elctions. It however doesnt plot for some states like California. I have checked data and FIPS codes seems to exist but still showing blank there. Any ideas what may be going on? I got county data from topo.json.
geo_data_c2 = [{'name': 'counties',
'url': county_topo,
'feature': 'us_counties.geo'}]
vis_election_counties = vincent.Map(data=merged, geo_data=geo_data_c2, scale=1000,
projection='albersUsa', data_bind='per_dem',
data_key='combined_fips', map_key={'counties': 'properties.FIPS'})
#Change our domain for an even inteager
vis_election_counties.scales['color'].domain = [0,1]
vis_election_counties.legend[![enter image description here][1]][1](title='per_dem')
vis_election_counties.to_json('vega.json')
vis_election_counties.display()
The FIPS codes for counties in the first ~7 states alphabetically need to be zero-padded to 5 characters.
Arapahoe County, CO has FIPS code 8005, which is represented as "08005" in https://raw.githubusercontent.com/jgoodall/us-maps/master/topojson/county.topo.json
merged['combined_fips'] = merged['combined_fips'].map(lambda i: str(i).zfill(5))
does anyone use arima.rob() function described by Eric Zivot and Jiahui Wang in { Modelling Financial Time Series with S-PLUS } ?
I have a question about it:
I used a dataset of network traffic flows that has anomaly, and I tried to predict the last part of dataset by robust ARIMA method (Arima.rob() function) .I compare this model with arima.mle of S-PLUS. But Unexpectedly, arima.rob’s prediction did not better than that.
I’m not sure my codes are correct and may be the reason of fault is my codes.
Please, help me if I used Arima.rob inappropriately?
tmp.rr<-arima.rob((tmh75)~1,p=2,d=1,q=2,freq=24,maxiter=4,max.fcal=80000)
tmp.for<-predict(tmp.rr,n.predict=10,newdata=df1,se=T)
plot(tmp.for,tmh75)
summary(tmp.for)
my code for classic arima:
`model <- list(list(order=c(2,1,2)),list(order=c(3,1,2),period=24))
fith <- arima.mle(tmh75-mean(tmh75),model=model)
foreh <- arima.forecast(tmh75,n=25,model=fith$model)
tsplot(tmh75,foreh$mean,foreh$mean+foreh$std.err,foreh$mean-foreh$std.err)
`
I want a rather simple (and cheap) solution, just for presentation purposes (and just to show the task duration bars - no connection lines between them). So, I am not interested in buying some advanced custom control like this for example. Have any of you ever used something like this? Are there any code samples available?
I would have pointed to Buck Woolley's dwExtreme site for an example of how to do a gantt in native DataWindow. However, "simple" I don't think is in your future if you want to roll your own. In fact, I'll be pleasantly surprised if someone writes a posting that includes a full description; I think it would take pages. (I'd be happy if someone proved me wrong.) In the meantime, here are some DataWindow basics I think you would need:
You can create an external DataWindow whose data source is not tied to a table
Columns in the data set do not have to be shown on the user interface
Columns in the data set can be used in expressions to evaluate attributes, so you could have a column for each of the following attributes of a rectangle:
x
width
color
I'd expect this to be a lot of work and time, and very likely to be worth the purchase the component (unless your time is valued at next to nothing, which in some IT shops is close to true).
Good luck,
Terry
(source: illudium.com)
You can make a simple Gantt chart with a Stacked Bar Graph (BarStacked (5) in the painter). The trick is to create a dummy series to space the bar out where you want it and make the dummy bar the same color as the graph's background (BackColor). It turns out you also need another dummy series with a small value to sit on the axis. Otherwise when you change the color of the bar that's doing the spacing, the axis line gets cut off. I found that .04 works well for this value.
Create the DataWindow
(This assumes familarity with the DataWindow Wizard. Refer to the PowerBuilder User's Guide for more information on creating graphs in DataWindows)
Click the icon for the new object wizard. Create a Graph DataWindow with an External data source. Create columns task type string(20), ser type string(1), and days type number. Set the Category to the task column and the Values to the days column. Click the Series button and select ser for the series. Don't bother with the title, and select the Stacked Bar graph type. When the painter opens, save the DataWindow. On the General tab in the Painter, change the Legend to None (0). On the Axis tab, select the Category axis, then set the sort to Unsorted (0). Select the Value axis then set the sort to Unsorted (0). Select the Series axis and set the sort to Ascending (1). Save the DataWindow.
Create the Window
Create a window and place a DataWindow control, dw_1. Set the data object to your graph DataWindow. Place the following in the open event (or pfc_postopen if using PFC).
try
dw_1.setRedraw(FALSE)
// LOAD DATA HERE
dw_1.object.gr_1.title = 'Project PBL Pusher'
dw_1.object.gr_1.category.label = 'Phase'
dw_1.object.gr_1.values.label = 'Project-Days'
catch (runtimeerror re)
if isvalid(gnv_app.inv_debug) then gnv_app.inv_debug.of_message(re.text) // could do better
finally
dw_1.setRedraw(TRUE)
end try
You would load the data for your chart where the comment says // LOAD DATA HERE
Script the graphcreate Event
Add an new event to dw_1. Select pbm_dwngraphcreate for the Event ID. I like to name these events by removing the pbm_dwn prefix so I use graphcreate. Add the following code to the event.
string ls_series
long li_color
try
li_color=long(dw_1.object.gr_1.backcolor)
// note first series is a dummy with a small value (0.04 seems to work) to keep the line from being hidden
ls_series = dw_1.seriesName("gr_1", 2)
if 0 = len(ls_series) then return // maybe show error message
// will return -1 when you set color same as the graph's backcolor but it sets the color
dw_1.setSeriesStyle("gr_1", ls_series, BackGround!, li_color) // the box
dw_1.setSeriesStyle("gr_1", ls_series, ForeGround!, li_color) // the inside
catch (runtimeerror re)
if isvalid(gnv_app.inv_debug) then gnv_app.inv_debug.of_message(re.text) // could do better
end try
Data for the Graph
Load the data with the categories in the reverse order of what you want. For each Task, insert 3 rows and set the series to a, b, and c, respectively. For series a in each task, set a small value. I used 0.04. You may have to experiment. For series b in each task, set the number of days before start. For series c, set the number of days. Below is the data in the sample DataWindow.
Task Ser Days
---- --- ----
Test a 0.04
Test b 24
Test c 10
Develop a 0.04
Develop b 10
Develop c 14
Design a 0.04
Design b 0
Design c 10
Sample DataWindow
Below is the source for a sample DataWindow in export format. You should be able to import into any version >= PB 10. Copy the code and paste it into a file with an SRD extension, then import it.
HA$PBExportHeader$d_graph.srd
release 10;
datawindow(units=0 timer_interval=0 color=1073741824 processing=3 HTMLDW=no print.printername="" print.documentname="" print.orientation = 1 print.margin.left = 110 print.margin.right = 110 print.margin.top = 96 print.margin.bottom = 96 print.paper.source = 0 print.paper.size = 0 print.canusedefaultprinter=yes print.prompt=no print.buttons=no print.preview.buttons=no print.cliptext=no print.overrideprintjob=no print.collate=yes hidegrayline=no )
summary(height=0 color="536870912" )
footer(height=0 color="536870912" )
detail(height=0 color="536870912" )
table(column=(type=char(10) updatewhereclause=yes name=task dbname="task" )
column=(type=char(1) updatewhereclause=yes name=ser dbname="ser" )
column=(type=number updatewhereclause=yes name=days dbname="days" )
)
data("Test","a", 0.04,"Test","b", 24,"Test","c", 10,"Develop","a", 0.04,"Develop","b", 10,"Develop","c", 14,"Design","a", 0.04,"Design","b", 0,"Design","c", 10,)
graph(band=background height="1232" width="2798" graphtype="5" perspective="2" rotation="-20" color="0" backcolor="16777215" shadecolor="8355711" range= 0 border="3" overlappercent="0" spacing="100" plotnulldata="0" elevation="20" depth="100"x="0" y="0" height="1232" width="2798" name=gr_1 visible="1" sizetodisplay=1 series="ser" category="task" values="days" title="Title" title.dispattr.backcolor="553648127" title.dispattr.alignment="2" title.dispattr.autosize="1" title.dispattr.font.charset="0" title.dispattr.font.escapement="0" title.dispattr.font.face="Tahoma" title.dispattr.font.family="2" title.dispattr.font.height="0" title.dispattr.font.italic="0" title.dispattr.font.orientation="0" title.dispattr.font.pitch="2" title.dispattr.font.strikethrough="0" title.dispattr.font.underline="0" title.dispattr.font.weight="700" title.dispattr.format="[general]" title.dispattr.textcolor="0" title.dispattr.displayexpression="title" legend="0" legend.dispattr.backcolor="536870912" legend.dispattr.alignment="0" legend.dispattr.autosize="1" legend.dispattr.font.charset="0" legend.dispattr.font.escapement="0" legend.dispattr.font.face="Tahoma" legend.dispattr.font.family="2" legend.dispattr.font.height="0" legend.dispattr.font.italic="0" legend.dispattr.font.orientation="0" legend.dispattr.font.pitch="2" legend.dispattr.font.strikethrough="0" legend.dispattr.font.underline="0" legend.dispattr.font.weight="400" legend.dispattr.format="[general]" legend.dispattr.textcolor="553648127" legend.dispattr.displayexpression="' '"
series.autoscale="1"
series.displayeverynlabels="0" series.droplines="0" series.frame="1" series.label="(None)" series.majordivisions="0" series.majorgridline="0" series.majortic="3" series.maximumvalue="0" series.minimumvalue="0" series.minordivisions="0" series.minorgridline="0" series.minortic="1" series.originline="1" series.primaryline="1" series.roundto="0" series.roundtounit="0" series.scaletype="1" series.scalevalue="1" series.secondaryline="0" series.shadebackedge="0" series.dispattr.backcolor="536870912" series.dispattr.alignment="0" series.dispattr.autosize="1" series.dispattr.font.charset="0" series.dispattr.font.escapement="0" series.dispattr.font.face="Tahoma" series.dispattr.font.family="2" series.dispattr.font.height="0" series.dispattr.font.italic="0" series.dispattr.font.orientation="0" series.dispattr.font.pitch="2" series.dispattr.font.strikethrough="0" series.dispattr.font.underline="0" series.dispattr.font.weight="400" series.dispattr.format="[general]" series.dispattr.textcolor="0" series.dispattr.displayexpression="series" series.labeldispattr.backcolor="553648127" series.labeldispattr.alignment="2" series.labeldispattr.autosize="1" series.labeldispattr.font.charset="0" series.labeldispattr.font.escapement="0" series.labeldispattr.font.face="Tahoma" series.labeldispattr.font.family="2" series.labeldispattr.font.height="0" series.labeldispattr.font.italic="0" series.labeldispattr.font.orientation="0" series.labeldispattr.font.pitch="2" series.labeldispattr.font.strikethrough="0" series.labeldispattr.font.underline="0" series.labeldispattr.font.weight="400" series.labeldispattr.format="[general]" series.labeldispattr.textcolor="0" series.labeldispattr.displayexpression=" seriesaxislabel" series.sort="1"
category.autoscale="1"
category.displayeverynlabels="0" category.droplines="0" category.frame="1" category.label="(None)" category.majordivisions="0" category.majorgridline="0" category.majortic="3" category.maximumvalue="0" category.minimumvalue="0" category.minordivisions="0" category.minorgridline="0" category.minortic="1" category.originline="0" category.primaryline="1" category.roundto="0" category.roundtounit="0" category.scaletype="1" category.scalevalue="1" category.secondaryline="0" category.shadebackedge="1" category.dispattr.backcolor="556870912" category.dispattr.alignment="1" category.dispattr.autosize="1" category.dispattr.font.charset="0" category.dispattr.font.escapement="0" category.dispattr.font.face="Tahoma" category.dispattr.font.family="2" category.dispattr.font.height="0" category.dispattr.font.italic="0" category.dispattr.font.orientation="0" category.dispattr.font.pitch="2" category.dispattr.font.strikethrough="0" category.dispattr.font.underline="0" category.dispattr.font.weight="400" category.dispattr.format="[general]" category.dispattr.textcolor="0" category.dispattr.displayexpression="category" category.labeldispattr.backcolor="556870912" category.labeldispattr.alignment="2" category.labeldispattr.autosize="1" category.labeldispattr.font.charset="0" category.labeldispattr.font.escapement="900" category.labeldispattr.font.face="Tahoma" category.labeldispattr.font.family="2" category.labeldispattr.font.height="0" category.labeldispattr.font.italic="0" category.labeldispattr.font.orientation="900" category.labeldispattr.font.pitch="2" category.labeldispattr.font.strikethrough="0" category.labeldispattr.font.underline="0" category.labeldispattr.font.weight="400" category.labeldispattr.format="[general]" category.labeldispattr.textcolor="0" category.labeldispattr.displayexpression="categoryaxislabel" category.sort="0"
values.autoscale="1"
values.displayeverynlabels="0" values.droplines="0" values.frame="1" values.label="(None)" values.majordivisions="0" values.majorgridline="0" values.majortic="3" values.maximumvalue="1500" values.minimumvalue="0" values.minordivisions="0" values.minorgridline="0" values.minortic="1" values.originline="1" values.primaryline="1" values.roundto="0" values.roundtounit="0" values.scaletype="1" values.scalevalue="1" values.secondaryline="0" values.shadebackedge="0" values.dispattr.backcolor="556870912" values.dispattr.alignment="2" values.dispattr.autosize="1" values.dispattr.font.charset="0" values.dispattr.font.escapement="0" values.dispattr.font.face="Tahoma" values.dispattr.font.family="2" values.dispattr.font.height="0" values.dispattr.font.italic="0" values.dispattr.font.orientation="0" values.dispattr.font.pitch="2" values.dispattr.font.strikethrough="0" values.dispattr.font.underline="0" values.dispattr.font.weight="400" values.dispattr.format="[General]" values.dispattr.textcolor="0" values.dispattr.displayexpression="value" values.labeldispattr.backcolor="553648127" values.labeldispattr.alignment="2" values.labeldispattr.autosize="1" values.labeldispattr.font.charset="0" values.labeldispattr.font.escapement="0" values.labeldispattr.font.face="Tahoma" values.labeldispattr.font.family="2" values.labeldispattr.font.height="0" values.labeldispattr.font.italic="0" values.labeldispattr.font.orientation="0" values.labeldispattr.font.pitch="2" values.labeldispattr.font.strikethrough="0" values.labeldispattr.font.underline="0" values.labeldispattr.font.weight="700" values.labeldispattr.format="[general]" values.labeldispattr.textcolor="0" values.labeldispattr.displayexpression="valuesaxislabel" )
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xhtmlgen() cssgen(sessionspecific="0" )
xmlgen(inline="0" )
xsltgen()
jsgen()
export.xml(headgroups="1" includewhitespace="0" metadatatype=0 savemetadata=0 )
import.xml()
export.pdf(method=0 distill.custompostscript="0" xslfop.print="0" )
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